Code

package kaggle;

import org.datavec.api.records.reader.RecordReader;
import org.datavec.api.records.reader.impl.csv.CSVRecordReader;
import org.datavec.api.split.FileSplit;
import org.deeplearning4j.arbiter.DL4JConfiguration;
import org.deeplearning4j.arbiter.MultiLayerSpace;
import org.deeplearning4j.arbiter.data.DataSetIteratorProvider;
import org.deeplearning4j.arbiter.layers.DenseLayerSpace;
import org.deeplearning4j.arbiter.layers.OutputLayerSpace;
import org.deeplearning4j.arbiter.optimize.api.CandidateGenerator;
import org.deeplearning4j.arbiter.optimize.api.OptimizationResult;
import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
import org.deeplearning4j.arbiter.optimize.api.data.DataProvider;
import org.deeplearning4j.arbiter.optimize.api.saving.ResultReference;
import org.deeplearning4j.arbiter.optimize.api.saving.ResultSaver;
import org.deeplearning4j.arbiter.optimize.api.score.ScoreFunction;
import org.deeplearning4j.arbiter.optimize.api.termination.MaxCandidatesCondition;
import org.deeplearning4j.arbiter.optimize.api.termination.MaxTimeCondition;
import org.deeplearning4j.arbiter.optimize.api.termination.TerminationCondition;
import org.deeplearning4j.arbiter.optimize.candidategenerator.RandomSearchGenerator;
import org.deeplearning4j.arbiter.optimize.config.OptimizationConfiguration;
import org.deeplearning4j.arbiter.optimize.parameter.continuous.ContinuousParameterSpace;
import org.deeplearning4j.arbiter.optimize.parameter.integer.IntegerParameterSpace;
import org.deeplearning4j.arbiter.optimize.runner.IOptimizationRunner;
import org.deeplearning4j.arbiter.optimize.runner.LocalOptimizationRunner;
import org.deeplearning4j.arbiter.optimize.runner.listener.runner.LoggingOptimizationRunnerStatusListener;
import org.deeplearning4j.arbiter.optimize.ui.ArbiterUIServer;
import org.deeplearning4j.arbiter.optimize.ui.listener.UIOptimizationRunnerStatusListener;
import org.deeplearning4j.arbiter.saver.local.multilayer.LocalMultiLayerNetworkSaver;
import org.deeplearning4j.arbiter.scoring.multilayer.TestSetAccuracyScoreFunction;
import org.deeplearning4j.arbiter.task.MultiLayerNetworkTaskCreator;
import org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator;
import org.deeplearning4j.datasets.iterator.IteratorDataSetIterator;
import org.deeplearning4j.datasets.iterator.MultipleEpochsIterator;
import org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator;
import org.deeplearning4j.nn.api.OptimizationAlgorithm;
import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
import org.deeplearning4j.nn.weights.WeightInit;
import org.nd4j.linalg.dataset.DataSet;
import org.nd4j.linalg.dataset.SplitTestAndTrain;
import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
import org.nd4j.linalg.dataset.api.iterator.TestDataSetIterator;
import org.nd4j.linalg.lossfunctions.LossFunctions;

import java.io.File;
import java.util.List;
import java.util.concurrent.TimeUnit;


/**
 * Created by danlin on 2016-07-15.
 */
public class TitanicOptimization {


    /**
     * This is a basic hyperparameter optimization example using Arbiter to conduct random search on two network hyperparameters.
     * The two hyperparameters are learning rate and layer size, and the search is conducted for a simple multi-layer perceptron
     * on MNIST data.
     *
     * Note that this example has a UI, but it (currently) does not start automatically.
     * By default, the UI is accessible at http://localhost:8080/arbiter
     *
     * @author Alex Black
     */

        public static void main(String[] args) throws Exception {

            ParameterSpace<Double> learningRateHyperparam = new ContinuousParameterSpace(0.01, 0.1);  //Values will be generated uniformly at random between 0.0001 and 0.1 (inclusive)
//            ParameterSpace<Integer> layerSizeHyperparam = new IntegerParameterSpace(2,12);            //Integer values will be generated uniformly at random between 16 and 256 (inclusive)
//            ParameterSpace<Integer> layerSizeHyperparam2 = new IntegerParameterSpace(2,12);            //Integer values will be generated uniformly at random between 16 and 256 (inclusive)

            MultiLayerSpace hyperparameterSpace = new MultiLayerSpace.Builder()
                    //These next few options: fixed values for all models
                    .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT)
                    .iterations(1)
                    .regularization(true)
                    .l2(1e-4)
                    .weightInit(WeightInit.XAVIER)
                    .activation("relu")
                    //Learning rate: this is something we want to test different values for
                    .learningRate(learningRateHyperparam)
                    .addLayer( new DenseLayerSpace.Builder()
                            .nIn(12)  //Fixed input: 12
                            .nOut(8)
                            .build())
                    .addLayer( new DenseLayerSpace.Builder()
                            .nIn(8)
                            .nOut(4)
                            .build())
                    .addLayer( new OutputLayerSpace.Builder()
                            .nIn(4)
                            .nOut(2)
                            .activation("softmax")
                            .lossFunction(LossFunctions.LossFunction.NEGATIVELOGLIKELIHOOD)
                            .build())
                    .pretrain(false).backprop(true).build();

            //Now: We need to define a few configuration options
            // (a) How are we going to generate candidates? (random search or grid search)
            CandidateGenerator<DL4JConfiguration> candidateGenerator = new RandomSearchGenerator<>(hyperparameterSpace);    //Alternatively: new GridSearchCandidateGenerator<>(hyperparameterSpace, 5, GridSearchCandidateGenerator.Mode.RandomOrder);

            // (b) How are going to provide data? For now, we'll use a simple built-in data provider for DataSetIterators

            RecordReader recordReader = new CSVRecordReader(0,",");
            recordReader.initialize(new FileSplit(new File("/Users/danlin/git/dl4j-lab/dl4j/src/main/resources/updated/train0.csv")));

            //Second: the RecordReaderDataSetIterator handles conversion to DataSet objects, ready for use in neural network
            int labelIndex = 0;     //5 values in each row of the iris.txt CSV: 4 input features followed by an integer label (class) index. Labels are the 5th value (index 4) in each row
            int numClasses = 2;     //2 classes (types of iris flowers) in the iris data set. Classes have integer values 0, 1 or 2
            int batchSize = 891;    //Iris data set: 150 examples total. We are loading all of them into one DataSet (not recommended for large data sets)

            DataSetIterator iterator = new RecordReaderDataSetIterator(recordReader,batchSize,labelIndex,numClasses);

            DataSet allData = iterator.next();
            allData.shuffle();
            SplitTestAndTrain testAndTrain = allData.splitTestAndTrain(0.65);  //Use 65% of data for training

            DataSetIterator titanicTrain = new MultipleEpochsIterator(5, new ListDataSetIterator(testAndTrain.getTrain().asList()));
            DataSetIterator titanicTest = new ListDataSetIterator(testAndTrain.getTest().asList());
            DataProvider<DataSetIterator> dataProvider = new DataSetIteratorProvider(titanicTrain, titanicTest);


            // (c) How we are going to save the models that are generated and tested?
            //     In this example, let's save them to disk the working directory
            //     This will result in examples being saved to arbiterExample/0/, arbiterExample/1/, arbiterExample/2/, ...
            String baseSaveDirectory = "arbiterExample/";
            File f = new File(baseSaveDirectory);
            if(f.exists()) f.delete();
            f.mkdir();
            ResultSaver<DL4JConfiguration,MultiLayerNetwork,Object> modelSaver = new LocalMultiLayerNetworkSaver<>(baseSaveDirectory);

            // (d) What are we actually trying to optimize?
            //     In this example, let's use classification accuracy on the test set
            ScoreFunction<MultiLayerNetwork,DataSetIterator> scoreFunction = new TestSetAccuracyScoreFunction();

            // (e) When should we stop searching? Specify this with termination conditions
            //     For this example, we are stopping the search at 15 minutes or 20 candidates - whichever comes first
            TerminationCondition[] terminationConditions = {new MaxTimeCondition(15, TimeUnit.MINUTES), new MaxCandidatesCondition(30)};



            //Given these configuration options, let's put them all together:
            OptimizationConfiguration<DL4JConfiguration, MultiLayerNetwork, DataSetIterator, Object> configuration
                    = new OptimizationConfiguration.Builder<DL4JConfiguration, MultiLayerNetwork, DataSetIterator, Object>()
                    .candidateGenerator(candidateGenerator)
                    .dataProvider(dataProvider)
                    .modelSaver(modelSaver)
                    .scoreFunction(scoreFunction)
                    .terminationConditions(terminationConditions)
                    .build();

            //And set up execution locally on this machine:
            IOptimizationRunner<DL4JConfiguration,MultiLayerNetwork,Object> runner
                    = new LocalOptimizationRunner<>(configuration, new MultiLayerNetworkTaskCreator<>());


            //Start the UI
            ArbiterUIServer server = ArbiterUIServer.getInstance();
            runner.addListeners(new UIOptimizationRunnerStatusListener(server));


            //Start the hyperparameter optimization
            runner.execute();


            //Print out some basic stats regarding the optimization procedure
            StringBuilder sb = new StringBuilder();
            sb.append("Best score: ").append(runner.bestScore()).append("\n")
                    .append("Index of model with best score: ").append(runner.bestScoreCandidateIndex()).append("\n")
                    .append("Number of configurations evaluated: ").append(runner.numCandidatesCompleted()).append("\n");
            System.out.println(sb.toString());


            //Get all results, and print out details of the best result:
            int indexOfBestResult = runner.bestScoreCandidateIndex();
            List<ResultReference<DL4JConfiguration,MultiLayerNetwork,Object>> allResults = runner.getResults();

            OptimizationResult<DL4JConfiguration,MultiLayerNetwork,Object> bestResult = allResults.get(indexOfBestResult).getResult();
            MultiLayerNetwork bestModel = bestResult.getResult();

            System.out.println("\n\nConfiguration of best model:\n");
            System.out.println(bestModel.getLayerWiseConfigurations().toJson());


            //Note: UI server will shut down once execution is complete, as JVM will exit
            //So do a Thread.sleep(1 minute) to keep JVM alive, so that network configurations can be viewed
            Thread.sleep(60000);
            System.exit(0);
        }

}

Input data

0,0,0,1,1,0,22,1,0,7.25,0,0,1
1,1,0,0,0,1,38,1,0,71.2833,1,0,0
1,0,0,1,0,1,26,0,0,7.925,0,0,1
1,1,0,0,0,1,35,1,0,53.1,0,0,1
0,0,0,1,1,0,35,0,0,8.05,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,8.4583,0,1,0
0,1,0,0,1,0,54,0,0,51.8625,0,0,1
0,0,0,1,1,0,2,3,1,21.075,0,0,1
1,0,0,1,0,1,27,0,2,11.1333,0,0,1
1,0,1,0,0,1,14,1,0,30.0708,1,0,0
1,0,0,1,0,1,4,1,1,16.7,0,0,1
1,1,0,0,0,1,58,0,0,26.55,0,0,1
0,0,0,1,1,0,20,0,0,8.05,0,0,1
0,0,0,1,1,0,39,1,5,31.275,0,0,1
0,0,0,1,0,1,14,0,0,7.8542,0,0,1
1,0,1,0,0,1,55,0,0,16,0,0,1
0,0,0,1,1,0,2,4,1,29.125,0,1,0
1,0,1,0,1,0,29.69911764705882,0,0,13,0,0,1
0,0,0,1,0,1,31,1,0,18,0,0,1
1,0,0,1,0,1,29.69911764705882,0,0,7.225,1,0,0
0,0,1,0,1,0,35,0,0,26,0,0,1
1,0,1,0,1,0,34,0,0,13,0,0,1
1,0,0,1,0,1,15,0,0,8.0292,0,1,0
1,1,0,0,1,0,28,0,0,35.5,0,0,1
0,0,0,1,0,1,8,3,1,21.075,0,0,1
1,0,0,1,0,1,38,1,5,31.3875,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.225,1,0,0
0,1,0,0,1,0,19,3,2,263,0,0,1
1,0,0,1,0,1,29.69911764705882,0,0,7.8792,0,1,0
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,0,0,1
0,1,0,0,1,0,40,0,0,27.7208,1,0,0
1,1,0,0,0,1,29.69911764705882,1,0,146.5208,1,0,0
1,0,0,1,0,1,29.69911764705882,0,0,7.75,0,1,0
0,0,1,0,1,0,66,0,0,10.5,0,0,1
0,1,0,0,1,0,28,1,0,82.1708,1,0,0
0,1,0,0,1,0,42,1,0,52,0,0,1
1,0,0,1,1,0,29.69911764705882,0,0,7.2292,1,0,0
0,0,0,1,1,0,21,0,0,8.05,0,0,1
0,0,0,1,0,1,18,2,0,18,0,0,1
1,0,0,1,0,1,14,1,0,11.2417,1,0,0
0,0,0,1,0,1,40,1,0,9.475,0,0,1
0,0,1,0,0,1,27,1,0,21,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,1,0,0
1,0,1,0,0,1,3,1,2,41.5792,1,0,0
1,0,0,1,0,1,19,0,0,7.8792,0,1,0
0,0,0,1,1,0,29.69911764705882,0,0,8.05,0,0,1
0,0,0,1,1,0,29.69911764705882,1,0,15.5,0,1,0
1,0,0,1,0,1,29.69911764705882,0,0,7.75,0,1,0
0,0,0,1,1,0,29.69911764705882,2,0,21.6792,1,0,0
0,0,0,1,0,1,18,1,0,17.8,0,0,1
0,0,0,1,1,0,7,4,1,39.6875,0,0,1
0,0,0,1,1,0,21,0,0,7.8,0,0,1
1,1,0,0,0,1,49,1,0,76.7292,1,0,0
1,0,1,0,0,1,29,1,0,26,0,0,1
0,1,0,0,1,0,65,0,1,61.9792,1,0,0
1,1,0,0,1,0,29.69911764705882,0,0,35.5,0,0,1
1,0,1,0,0,1,21,0,0,10.5,0,0,1
0,0,0,1,1,0,28.5,0,0,7.2292,1,0,0
1,0,1,0,0,1,5,1,2,27.75,0,0,1
0,0,0,1,1,0,11,5,2,46.9,0,0,1
0,0,0,1,1,0,22,0,0,7.2292,1,0,0
1,1,0,0,0,1,38,0,0,80,0,0,1
0,1,0,0,1,0,45,1,0,83.475,0,0,1
0,0,0,1,1,0,4,3,2,27.9,0,0,1
0,1,0,0,1,0,29.69911764705882,0,0,27.7208,1,0,0
1,0,0,1,1,0,29.69911764705882,1,1,15.2458,1,0,0
1,0,1,0,0,1,29,0,0,10.5,0,0,1
0,0,0,1,1,0,19,0,0,8.1583,0,0,1
1,0,0,1,0,1,17,4,2,7.925,0,0,1
0,0,0,1,1,0,26,2,0,8.6625,0,0,1
0,0,1,0,1,0,32,0,0,10.5,0,0,1
0,0,0,1,0,1,16,5,2,46.9,0,0,1
0,0,1,0,1,0,21,0,0,73.5,0,0,1
0,0,0,1,1,0,26,1,0,14.4542,1,0,0
1,0,0,1,1,0,32,0,0,56.4958,0,0,1
0,0,0,1,1,0,25,0,0,7.65,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,8.05,0,0,1
1,0,1,0,1,0,0.83,0,2,29,0,0,1
1,0,0,1,0,1,30,0,0,12.475,0,0,1
0,0,0,1,1,0,22,0,0,9,0,0,1
1,0,0,1,1,0,29,0,0,9.5,0,0,1
1,0,0,1,0,1,29.69911764705882,0,0,7.7875,0,1,0
0,1,0,0,1,0,28,0,0,47.1,0,0,1
1,0,1,0,0,1,17,0,0,10.5,0,0,1
1,0,0,1,0,1,33,3,0,15.85,0,0,1
0,0,0,1,1,0,16,1,3,34.375,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,8.05,0,0,1
1,1,0,0,0,1,23,3,2,263,0,0,1
0,0,0,1,1,0,24,0,0,8.05,0,0,1
0,0,0,1,1,0,29,0,0,8.05,0,0,1
0,0,0,1,1,0,20,0,0,7.8542,0,0,1
0,1,0,0,1,0,46,1,0,61.175,0,0,1
0,0,0,1,1,0,26,1,2,20.575,0,0,1
0,0,0,1,1,0,59,0,0,7.25,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,8.05,0,0,1
0,1,0,0,1,0,71,0,0,34.6542,1,0,0
1,1,0,0,1,0,23,0,1,63.3583,1,0,0
1,0,1,0,0,1,34,0,1,23,0,0,1
0,0,1,0,1,0,34,1,0,26,0,0,1
0,0,0,1,0,1,28,0,0,7.8958,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,0,0,1
0,1,0,0,1,0,21,0,1,77.2875,0,0,1
0,0,0,1,1,0,33,0,0,8.6542,0,0,1
0,0,0,1,1,0,37,2,0,7.925,0,0,1
0,0,0,1,1,0,28,0,0,7.8958,0,0,1
1,0,0,1,0,1,21,0,0,7.65,0,0,1
1,0,0,1,1,0,29.69911764705882,0,0,7.775,0,0,1
0,0,0,1,1,0,38,0,0,7.8958,0,0,1
1,0,0,1,0,1,29.69911764705882,1,0,24.15,0,1,0
0,1,0,0,1,0,47,0,0,52,0,0,1
0,0,0,1,0,1,14.5,1,0,14.4542,1,0,0
0,0,0,1,1,0,22,0,0,8.05,0,0,1
0,0,0,1,0,1,20,1,0,9.825,0,0,1
0,0,0,1,0,1,17,0,0,14.4583,1,0,0
0,0,0,1,1,0,21,0,0,7.925,0,0,1
0,0,0,1,1,0,70.5,0,0,7.75,0,1,0
0,0,1,0,1,0,29,1,0,21,0,0,1
0,1,0,0,1,0,24,0,1,247.5208,1,0,0
0,0,0,1,0,1,2,4,2,31.275,0,0,1
0,0,1,0,1,0,21,2,0,73.5,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,8.05,0,0,1
0,0,1,0,1,0,32.5,1,0,30.0708,1,0,0
1,0,1,0,0,1,32.5,0,0,13,0,0,1
0,1,0,0,1,0,54,0,1,77.2875,0,0,1
1,0,0,1,1,0,12,1,0,11.2417,1,0,0
0,0,0,1,1,0,29.69911764705882,0,0,7.75,0,1,0
1,0,0,1,1,0,24,0,0,7.1417,0,0,1
1,0,0,1,0,1,29.69911764705882,1,1,22.3583,1,0,0
0,0,0,1,1,0,45,0,0,6.975,0,0,1
0,0,0,1,1,0,33,0,0,7.8958,1,0,0
0,0,0,1,1,0,20,0,0,7.05,0,0,1
0,0,0,1,0,1,47,1,0,14.5,0,0,1
1,0,1,0,0,1,29,1,0,26,0,0,1
0,0,1,0,1,0,25,0,0,13,0,0,1
0,0,1,0,1,0,23,0,0,15.0458,1,0,0
1,1,0,0,0,1,19,0,2,26.2833,0,0,1
0,1,0,0,1,0,37,1,0,53.1,0,0,1
0,0,0,1,1,0,16,0,0,9.2167,0,0,1
0,1,0,0,1,0,24,0,0,79.2,1,0,0
0,0,0,1,0,1,29.69911764705882,0,2,15.2458,1,0,0
1,0,0,1,0,1,22,0,0,7.75,0,0,1
1,0,0,1,0,1,24,1,0,15.85,0,0,1
0,0,0,1,1,0,19,0,0,6.75,0,1,0
0,0,1,0,1,0,18,0,0,11.5,0,0,1
0,0,1,0,1,0,19,1,1,36.75,0,0,1
1,0,0,1,1,0,27,0,0,7.7958,0,0,1
0,0,0,1,0,1,9,2,2,34.375,0,0,1
0,0,1,0,1,0,36.5,0,2,26,0,0,1
0,0,1,0,1,0,42,0,0,13,0,0,1
0,0,1,0,1,0,51,0,0,12.525,0,0,1
1,1,0,0,0,1,22,1,0,66.6,0,0,1
0,0,0,1,1,0,55.5,0,0,8.05,0,0,1
0,0,0,1,1,0,40.5,0,2,14.5,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.3125,0,0,1
0,1,0,0,1,0,51,0,1,61.3792,1,0,0
1,0,0,1,0,1,16,0,0,7.7333,0,1,0
0,0,0,1,1,0,30,0,0,8.05,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,8.6625,0,0,1
0,0,0,1,1,0,29.69911764705882,8,2,69.55,0,0,1
0,0,0,1,1,0,44,0,1,16.1,0,0,1
1,0,1,0,0,1,40,0,0,15.75,0,0,1
0,0,0,1,1,0,26,0,0,7.775,0,0,1
0,0,0,1,1,0,17,0,0,8.6625,0,0,1
0,0,0,1,1,0,1,4,1,39.6875,0,0,1
1,0,0,1,1,0,9,0,2,20.525,0,0,1
1,1,0,0,0,1,29.69911764705882,0,1,55,0,0,1
0,0,0,1,0,1,45,1,4,27.9,0,0,1
0,1,0,0,1,0,29.69911764705882,0,0,25.925,0,0,1
0,0,0,1,1,0,28,0,0,56.4958,0,0,1
0,1,0,0,1,0,61,0,0,33.5,0,0,1
0,0,0,1,1,0,4,4,1,29.125,0,1,0
1,0,0,1,0,1,1,1,1,11.1333,0,0,1
0,0,0,1,1,0,21,0,0,7.925,0,0,1
0,1,0,0,1,0,56,0,0,30.6958,1,0,0
0,0,0,1,1,0,18,1,1,7.8542,0,0,1
0,0,0,1,1,0,29.69911764705882,3,1,25.4667,0,0,1
0,1,0,0,0,1,50,0,0,28.7125,1,0,0
0,0,1,0,1,0,30,0,0,13,0,0,1
0,0,0,1,1,0,36,0,0,0,0,0,1
0,0,0,1,0,1,29.69911764705882,8,2,69.55,0,0,1
0,0,1,0,1,0,29.69911764705882,0,0,15.05,1,0,0
0,0,0,1,1,0,9,4,2,31.3875,0,0,1
1,0,1,0,1,0,1,2,1,39,0,0,1
1,0,0,1,0,1,4,0,2,22.025,0,0,1
0,1,0,0,1,0,29.69911764705882,0,0,50,0,0,1
1,0,0,1,0,1,29.69911764705882,1,0,15.5,0,1,0
1,1,0,0,1,0,45,0,0,26.55,0,0,1
0,0,0,1,1,0,40,1,1,15.5,0,1,0
0,0,0,1,1,0,36,0,0,7.8958,0,0,1
1,0,1,0,0,1,32,0,0,13,0,0,1
0,0,1,0,1,0,19,0,0,13,0,0,1
1,0,0,1,0,1,19,1,0,7.8542,0,0,1
1,0,1,0,1,0,3,1,1,26,0,0,1
1,1,0,0,0,1,44,0,0,27.7208,1,0,0
1,1,0,0,0,1,58,0,0,146.5208,1,0,0
0,0,0,1,1,0,29.69911764705882,0,0,7.75,0,1,0
0,0,0,1,1,0,42,0,1,8.4042,0,0,1
1,0,0,1,0,1,29.69911764705882,0,0,7.75,0,1,0
0,0,1,0,0,1,24,0,0,13,0,0,1
0,0,0,1,1,0,28,0,0,9.5,0,0,1
0,0,0,1,1,0,29.69911764705882,8,2,69.55,0,0,1
0,0,0,1,1,0,34,0,0,6.4958,0,0,1
0,0,0,1,1,0,45.5,0,0,7.225,1,0,0
1,0,0,1,1,0,18,0,0,8.05,0,0,1
0,0,0,1,0,1,2,0,1,10.4625,0,0,1
0,0,0,1,1,0,32,1,0,15.85,0,0,1
1,0,0,1,1,0,26,0,0,18.7875,1,0,0
1,0,0,1,0,1,16,0,0,7.75,0,1,0
1,1,0,0,1,0,40,0,0,31,1,0,0
0,0,0,1,1,0,24,0,0,7.05,0,0,1
1,0,1,0,0,1,35,0,0,21,0,0,1
0,0,0,1,1,0,22,0,0,7.25,0,0,1
0,0,1,0,1,0,30,0,0,13,0,0,1
0,0,0,1,1,0,29.69911764705882,1,0,7.75,0,1,0
1,1,0,0,0,1,31,1,0,113.275,1,0,0
1,0,0,1,0,1,27,0,0,7.925,0,0,1
0,0,1,0,1,0,42,1,0,27,0,0,1
1,1,0,0,0,1,32,0,0,76.2917,1,0,0
0,0,1,0,1,0,30,0,0,10.5,0,0,1
1,0,0,1,1,0,16,0,0,8.05,0,0,1
0,0,1,0,1,0,27,0,0,13,0,0,1
0,0,0,1,1,0,51,0,0,8.05,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,0,0,1
1,1,0,0,1,0,38,1,0,90,0,0,1
0,0,0,1,1,0,22,0,0,9.35,0,0,1
1,0,1,0,1,0,19,0,0,10.5,0,0,1
0,0,0,1,1,0,20.5,0,0,7.25,0,0,1
0,0,1,0,1,0,18,0,0,13,0,0,1
0,0,0,1,0,1,29.69911764705882,3,1,25.4667,0,0,1
1,1,0,0,0,1,35,1,0,83.475,0,0,1
0,0,0,1,1,0,29,0,0,7.775,0,0,1
0,0,1,0,1,0,59,0,0,13.5,0,0,1
1,0,0,1,0,1,5,4,2,31.3875,0,0,1
0,0,1,0,1,0,24,0,0,10.5,0,0,1
0,0,0,1,0,1,29.69911764705882,0,0,7.55,0,0,1
0,0,1,0,1,0,44,1,0,26,0,0,1
1,0,1,0,0,1,8,0,2,26.25,0,0,1
0,0,1,0,1,0,19,0,0,10.5,0,0,1
0,0,1,0,1,0,33,0,0,12.275,0,0,1
0,0,0,1,0,1,29.69911764705882,1,0,14.4542,1,0,0
1,0,0,1,0,1,29.69911764705882,1,0,15.5,0,1,0
0,0,1,0,1,0,29,0,0,10.5,0,0,1
0,0,0,1,1,0,22,0,0,7.125,0,0,1
0,0,0,1,1,0,30,0,0,7.225,1,0,0
0,1,0,0,1,0,44,2,0,90,0,1,0
0,0,0,1,0,1,25,0,0,7.775,0,0,1
1,0,1,0,0,1,24,0,2,14.5,0,0,1
1,1,0,0,1,0,37,1,1,52.5542,0,0,1
0,0,1,0,1,0,54,1,0,26,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.25,0,0,1
0,0,0,1,0,1,29,1,1,10.4625,0,0,1
0,1,0,0,1,0,62,0,0,26.55,0,0,1
0,0,0,1,1,0,30,1,0,16.1,0,0,1
0,0,0,1,0,1,41,0,2,20.2125,0,0,1
1,0,0,1,0,1,29,0,2,15.2458,1,0,0
1,1,0,0,0,1,29.69911764705882,0,0,79.2,1,0,0
1,1,0,0,0,1,30,0,0,86.5,0,0,1
1,1,0,0,0,1,35,0,0,512.3292,1,0,0
1,0,1,0,0,1,50,0,1,26,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.75,0,1,0
1,0,0,1,1,0,3,4,2,31.3875,0,0,1
0,1,0,0,1,0,52,1,1,79.65,0,0,1
0,1,0,0,1,0,40,0,0,0,0,0,1
0,0,0,1,0,1,29.69911764705882,0,0,7.75,0,1,0
0,0,1,0,1,0,36,0,0,10.5,0,0,1
0,0,0,1,1,0,16,4,1,39.6875,0,0,1
1,0,0,1,1,0,25,1,0,7.775,0,0,1
1,1,0,0,0,1,58,0,1,153.4625,0,0,1
1,1,0,0,0,1,35,0,0,135.6333,0,0,1
0,1,0,0,1,0,29.69911764705882,0,0,31,0,0,1
1,0,0,1,1,0,25,0,0,0,0,0,1
1,0,1,0,0,1,41,0,1,19.5,0,0,1
0,1,0,0,1,0,37,0,1,29.7,1,0,0
1,0,0,1,0,1,29.69911764705882,0,0,7.75,0,1,0
1,1,0,0,0,1,63,1,0,77.9583,0,0,1
0,0,0,1,0,1,45,0,0,7.75,0,0,1
0,0,1,0,1,0,29.69911764705882,0,0,0,0,0,1
0,0,0,1,1,0,7,4,1,29.125,0,1,0
1,0,0,1,0,1,35,1,1,20.25,0,0,1
0,0,0,1,1,0,65,0,0,7.75,0,1,0
0,0,0,1,1,0,28,0,0,7.8542,0,0,1
0,0,0,1,1,0,16,0,0,9.5,0,0,1
1,0,0,1,1,0,19,0,0,8.05,0,0,1
0,1,0,0,1,0,29.69911764705882,0,0,26,0,0,1
0,0,0,1,1,0,33,0,0,8.6625,1,0,0
1,0,0,1,1,0,30,0,0,9.5,0,0,1
0,0,0,1,1,0,22,0,0,7.8958,0,0,1
1,0,1,0,1,0,42,0,0,13,0,0,1
1,0,0,1,0,1,22,0,0,7.75,0,1,0
1,1,0,0,0,1,26,0,0,78.85,0,0,1
1,1,0,0,0,1,19,1,0,91.0792,1,0,0
0,0,1,0,1,0,36,0,0,12.875,1,0,0
0,0,0,1,0,1,24,0,0,8.85,0,0,1
0,0,0,1,1,0,24,0,0,7.8958,0,0,1
0,1,0,0,1,0,29.69911764705882,0,0,27.7208,1,0,0
0,0,0,1,1,0,23.5,0,0,7.2292,1,0,0
0,1,0,0,0,1,2,1,2,151.55,0,0,1
1,1,0,0,1,0,29.69911764705882,0,0,30.5,0,0,1
1,1,0,0,0,1,50,0,1,247.5208,1,0,0
1,0,0,1,0,1,29.69911764705882,0,0,7.75,0,1,0
1,0,0,1,1,0,29.69911764705882,2,0,23.25,0,1,0
0,0,0,1,1,0,19,0,0,0,0,0,1
1,0,1,0,0,1,29.69911764705882,0,0,12.35,0,1,0
0,0,0,1,1,0,29.69911764705882,0,0,8.05,0,0,1
1,1,0,0,1,0,0.92,1,2,151.55,0,0,1
1,1,0,0,0,1,29.69911764705882,0,0,110.8833,1,0,0
1,1,0,0,0,1,17,1,0,108.9,1,0,0
0,0,1,0,1,0,30,1,0,24,1,0,0
1,1,0,0,0,1,30,0,0,56.9292,1,0,0
1,1,0,0,0,1,24,0,0,83.1583,1,0,0
1,1,0,0,0,1,18,2,2,262.375,1,0,0
0,0,1,0,0,1,26,1,1,26,0,0,1
0,0,0,1,1,0,28,0,0,7.8958,0,0,1
0,0,1,0,1,0,43,1,1,26.25,0,0,1
1,0,0,1,0,1,26,0,0,7.8542,0,0,1
1,0,1,0,0,1,24,1,0,26,0,0,1
0,0,1,0,1,0,54,0,0,14,0,0,1
1,1,0,0,0,1,31,0,2,164.8667,0,0,1
1,1,0,0,0,1,40,1,1,134.5,1,0,0
0,0,0,1,1,0,22,0,0,7.25,0,0,1
0,0,0,1,1,0,27,0,0,7.8958,0,0,1
1,0,1,0,0,1,30,0,0,12.35,0,1,0
1,0,1,0,0,1,22,1,1,29,0,0,1
0,0,0,1,1,0,29.69911764705882,8,2,69.55,0,0,1
1,1,0,0,0,1,36,0,0,135.6333,1,0,0
0,0,0,1,1,0,61,0,0,6.2375,0,0,1
1,0,1,0,0,1,36,0,0,13,0,0,1
1,0,0,1,0,1,31,1,1,20.525,0,0,1
1,1,0,0,0,1,16,0,1,57.9792,1,0,0
1,0,0,1,0,1,29.69911764705882,2,0,23.25,0,1,0
0,1,0,0,1,0,45.5,0,0,28.5,0,0,1
0,1,0,0,1,0,38,0,1,153.4625,0,0,1
0,0,0,1,1,0,16,2,0,18,0,0,1
1,1,0,0,0,1,29.69911764705882,1,0,133.65,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,0,0,1
0,1,0,0,1,0,29,1,0,66.6,0,0,1
1,1,0,0,0,1,41,0,0,134.5,1,0,0
1,0,0,1,1,0,45,0,0,8.05,0,0,1
0,1,0,0,1,0,45,0,0,35.5,0,0,1
1,0,1,0,1,0,2,1,1,26,0,0,1
1,1,0,0,0,1,24,3,2,263,0,0,1
0,0,1,0,1,0,28,0,0,13,0,0,1
0,0,1,0,1,0,25,0,0,13,0,0,1
0,0,1,0,1,0,36,0,0,13,0,0,1
1,0,1,0,0,1,24,0,0,13,0,0,1
1,0,1,0,0,1,40,0,0,13,0,0,1
1,0,0,1,0,1,29.69911764705882,1,0,16.1,0,0,1
1,0,0,1,1,0,3,1,1,15.9,0,0,1
0,0,0,1,1,0,42,0,0,8.6625,0,0,1
0,0,0,1,1,0,23,0,0,9.225,0,0,1
0,1,0,0,1,0,29.69911764705882,0,0,35,0,0,1
0,0,0,1,1,0,15,1,1,7.2292,1,0,0
0,0,0,1,1,0,25,1,0,17.8,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.225,1,0,0
0,0,0,1,1,0,28,0,0,9.5,0,0,1
1,1,0,0,0,1,22,0,1,55,0,0,1
0,0,1,0,0,1,38,0,0,13,0,0,1
1,0,0,1,0,1,29.69911764705882,0,0,7.8792,0,1,0
1,0,0,1,0,1,29.69911764705882,0,0,7.8792,0,1,0
0,0,0,1,1,0,40,1,4,27.9,0,0,1
0,0,1,0,1,0,29,1,0,27.7208,1,0,0
0,0,0,1,0,1,45,0,1,14.4542,1,0,0
0,0,0,1,1,0,35,0,0,7.05,0,0,1
0,0,0,1,1,0,29.69911764705882,1,0,15.5,0,1,0
0,0,0,1,1,0,30,0,0,7.25,0,0,1
1,1,0,0,0,1,60,1,0,75.25,1,0,0
1,0,0,1,0,1,29.69911764705882,0,0,7.2292,1,0,0
1,0,0,1,0,1,29.69911764705882,0,0,7.75,0,1,0
1,1,0,0,0,1,24,0,0,69.3,1,0,0
1,1,0,0,1,0,25,1,0,55.4417,1,0,0
0,0,0,1,1,0,18,1,0,6.4958,0,0,1
0,0,0,1,1,0,19,0,0,8.05,0,0,1
0,1,0,0,1,0,22,0,0,135.6333,1,0,0
0,0,0,1,0,1,3,3,1,21.075,0,0,1
1,1,0,0,0,1,29.69911764705882,1,0,82.1708,1,0,0
1,0,0,1,0,1,22,0,0,7.25,0,0,1
0,1,0,0,1,0,27,0,2,211.5,1,0,0
0,0,0,1,1,0,20,0,0,4.0125,1,0,0
0,0,0,1,1,0,19,0,0,7.775,0,0,1
1,1,0,0,0,1,42,0,0,227.525,1,0,0
1,0,0,1,0,1,1,0,2,15.7417,1,0,0
0,0,0,1,1,0,32,0,0,7.925,0,0,1
1,1,0,0,0,1,35,1,0,52,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,0,0,1
0,0,1,0,1,0,18,0,0,73.5,0,0,1
0,0,0,1,1,0,1,5,2,46.9,0,0,1
1,0,1,0,0,1,36,0,0,13,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.7292,0,1,0
1,0,1,0,0,1,17,0,0,12,1,0,0
1,1,0,0,1,0,36,1,2,120,0,0,1
1,0,0,1,1,0,21,0,0,7.7958,0,0,1
0,0,0,1,1,0,28,2,0,7.925,0,0,1
1,1,0,0,0,1,23,1,0,113.275,1,0,0
1,0,0,1,0,1,24,0,2,16.7,0,0,1
0,0,0,1,1,0,22,0,0,7.7958,0,0,1
0,0,0,1,0,1,31,0,0,7.8542,0,0,1
0,0,1,0,1,0,46,0,0,26,0,0,1
0,0,1,0,1,0,23,0,0,10.5,0,0,1
1,0,1,0,0,1,28,0,0,12.65,0,0,1
1,0,0,1,1,0,39,0,0,7.925,0,0,1
0,0,0,1,1,0,26,0,0,8.05,0,0,1
0,0,0,1,0,1,21,1,0,9.825,0,0,1
0,0,0,1,1,0,28,1,0,15.85,0,0,1
0,0,0,1,0,1,20,0,0,8.6625,0,0,1
0,0,1,0,1,0,34,1,0,21,0,0,1
0,0,0,1,1,0,51,0,0,7.75,0,0,1
1,0,1,0,1,0,3,1,1,18.75,0,0,1
0,0,0,1,1,0,21,0,0,7.775,0,0,1
0,0,0,1,0,1,29.69911764705882,3,1,25.4667,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,6.8583,0,1,0
1,1,0,0,0,1,33,1,0,90,0,1,0
0,0,1,0,1,0,29.69911764705882,0,0,0,0,0,1
1,0,0,1,1,0,44,0,0,7.925,0,0,1
0,0,0,1,0,1,29.69911764705882,0,0,8.05,0,0,1
1,0,1,0,0,1,34,1,1,32.5,0,0,1
1,0,1,0,0,1,18,0,2,13,0,0,1
0,0,1,0,1,0,30,0,0,13,0,0,1
0,0,0,1,0,1,10,0,2,24.15,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,1,0,0
0,0,0,1,1,0,21,0,0,7.7333,0,1,0
0,0,0,1,1,0,29,0,0,7.875,0,0,1
0,0,0,1,0,1,28,1,1,14.4,0,0,1
0,0,0,1,1,0,18,1,1,20.2125,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.25,0,0,1
1,0,1,0,0,1,28,1,0,26,0,0,1
1,0,1,0,0,1,19,0,0,26,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.75,0,1,0
1,0,0,1,1,0,32,0,0,8.05,0,0,1
1,1,0,0,1,0,28,0,0,26.55,0,0,1
1,0,0,1,0,1,29.69911764705882,1,0,16.1,0,0,1
1,0,1,0,0,1,42,1,0,26,0,0,1
0,0,0,1,1,0,17,0,0,7.125,0,0,1
0,1,0,0,1,0,50,1,0,55.9,0,0,1
1,1,0,0,0,1,14,1,2,120,0,0,1
0,0,0,1,0,1,21,2,2,34.375,0,0,1
1,0,1,0,0,1,24,2,3,18.75,0,0,1
0,1,0,0,1,0,64,1,4,263,0,0,1
0,0,1,0,1,0,31,0,0,10.5,0,0,1
1,0,1,0,0,1,45,1,1,26.25,0,0,1
0,0,0,1,1,0,20,0,0,9.5,0,0,1
0,0,0,1,1,0,25,1,0,7.775,0,0,1
1,0,1,0,0,1,28,0,0,13,0,0,1
1,0,0,1,1,0,29.69911764705882,0,0,8.1125,0,0,1
1,1,0,0,1,0,4,0,2,81.8583,0,0,1
1,0,1,0,0,1,13,0,1,19.5,0,0,1
1,1,0,0,1,0,34,0,0,26.55,0,0,1
1,0,0,1,0,1,5,2,1,19.2583,1,0,0
1,1,0,0,1,0,52,0,0,30.5,0,0,1
0,0,1,0,1,0,36,1,2,27.75,0,0,1
0,0,0,1,1,0,29.69911764705882,1,0,19.9667,0,0,1
0,1,0,0,1,0,30,0,0,27.75,1,0,0
1,1,0,0,1,0,49,1,0,89.1042,1,0,0
0,0,0,1,1,0,29.69911764705882,0,0,8.05,0,0,1
1,0,0,1,1,0,29,0,0,7.8958,1,0,0
0,1,0,0,1,0,65,0,0,26.55,0,0,1
1,1,0,0,0,1,29.69911764705882,1,0,51.8625,0,0,1
1,0,1,0,0,1,50,0,0,10.5,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.75,0,1,0
1,1,0,0,1,0,48,0,0,26.55,0,0,1
0,0,0,1,1,0,34,0,0,8.05,0,0,1
0,1,0,0,1,0,47,0,0,38.5,0,0,1
0,0,1,0,1,0,48,0,0,13,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,8.05,0,0,1
0,0,0,1,1,0,38,0,0,7.05,0,0,1
0,0,1,0,1,0,29.69911764705882,0,0,0,0,0,1
0,1,0,0,1,0,56,0,0,26.55,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.725,0,1,0
1,0,0,1,0,1,0.75,2,1,19.2583,1,0,0
0,0,0,1,1,0,29.69911764705882,0,0,7.25,0,0,1
0,0,0,1,1,0,38,0,0,8.6625,0,0,1
1,0,1,0,0,1,33,1,2,27.75,0,0,1
1,0,1,0,0,1,23,0,0,13.7917,1,0,0
0,0,0,1,0,1,22,0,0,9.8375,0,0,1
0,1,0,0,1,0,29.69911764705882,0,0,52,0,0,1
0,0,1,0,1,0,34,1,0,21,0,0,1
0,0,0,1,1,0,29,1,0,7.0458,0,0,1
0,0,0,1,1,0,22,0,0,7.5208,0,0,1
1,0,0,1,0,1,2,0,1,12.2875,0,0,1
0,0,0,1,1,0,9,5,2,46.9,0,0,1
0,0,1,0,1,0,29.69911764705882,0,0,0,0,0,1
0,0,0,1,1,0,50,0,0,8.05,0,0,1
1,0,0,1,0,1,63,0,0,9.5875,0,0,1
1,1,0,0,1,0,25,1,0,91.0792,1,0,0
0,0,0,1,0,1,29.69911764705882,3,1,25.4667,0,0,1
1,1,0,0,0,1,35,1,0,90,0,0,1
0,1,0,0,1,0,58,0,0,29.7,1,0,0
0,0,0,1,1,0,30,0,0,8.05,0,0,1
1,0,0,1,1,0,9,1,1,15.9,0,0,1
0,0,0,1,1,0,29.69911764705882,1,0,19.9667,0,0,1
0,0,0,1,1,0,21,0,0,7.25,0,0,1
0,1,0,0,1,0,55,0,0,30.5,0,0,1
0,1,0,0,1,0,71,0,0,49.5042,1,0,0
0,0,0,1,1,0,21,0,0,8.05,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,14.4583,1,0,0
1,1,0,0,0,1,54,1,0,78.2667,1,0,0
0,0,0,1,1,0,29.69911764705882,0,0,15.1,0,0,1
0,1,0,0,0,1,25,1,2,151.55,0,0,1
0,0,0,1,1,0,24,0,0,7.7958,0,0,1
0,0,0,1,1,0,17,0,0,8.6625,0,0,1
0,0,0,1,0,1,21,0,0,7.75,0,1,0
0,0,0,1,0,1,29.69911764705882,0,0,7.6292,0,1,0
0,0,0,1,0,1,37,0,0,9.5875,0,0,1
1,1,0,0,0,1,16,0,0,86.5,0,0,1
0,1,0,0,1,0,18,1,0,108.9,1,0,0
1,0,1,0,0,1,33,0,2,26,0,0,1
1,1,0,0,1,0,29.69911764705882,0,0,26.55,0,0,1
0,0,0,1,1,0,28,0,0,22.525,0,0,1
1,0,0,1,1,0,26,0,0,56.4958,0,0,1
1,0,0,1,1,0,29,0,0,7.75,0,1,0
0,0,0,1,1,0,29.69911764705882,0,0,8.05,0,0,1
1,1,0,0,1,0,36,0,0,26.2875,0,0,1
1,1,0,0,0,1,54,1,0,59.4,1,0,0
0,0,0,1,1,0,24,0,0,7.4958,0,0,1
0,1,0,0,1,0,47,0,0,34.0208,0,0,1
1,0,1,0,0,1,34,0,0,10.5,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,24.15,0,1,0
1,0,1,0,0,1,36,1,0,26,0,0,1
0,0,0,1,1,0,32,0,0,7.8958,0,0,1
1,1,0,0,0,1,30,0,0,93.5,0,0,1
0,0,0,1,1,0,22,0,0,7.8958,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.225,1,0,0
1,1,0,0,0,1,44,0,1,57.9792,1,0,0
0,0,0,1,1,0,29.69911764705882,0,0,7.2292,1,0,0
0,0,0,1,1,0,40.5,0,0,7.75,0,1,0
1,0,1,0,0,1,50,0,0,10.5,0,0,1
0,1,0,0,1,0,29.69911764705882,0,0,221.7792,0,0,1
0,0,0,1,1,0,39,0,0,7.925,0,0,1
0,0,1,0,1,0,23,2,1,11.5,0,0,1
1,0,1,0,0,1,2,1,1,26,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.2292,1,0,0
0,0,0,1,1,0,17,1,1,7.2292,1,0,0
1,0,0,1,0,1,29.69911764705882,0,2,22.3583,1,0,0
0,0,0,1,0,1,30,0,0,8.6625,0,0,1
1,0,1,0,0,1,7,0,2,26.25,0,0,1
0,1,0,0,1,0,45,0,0,26.55,0,0,1
1,1,0,0,0,1,30,0,0,106.425,1,0,0
0,0,0,1,1,0,29.69911764705882,0,0,14.5,0,0,1
1,1,0,0,0,1,22,0,2,49.5,1,0,0
1,1,0,0,0,1,36,0,2,71,0,0,1
0,0,0,1,0,1,9,4,2,31.275,0,0,1
0,0,0,1,0,1,11,4,2,31.275,0,0,1
1,0,1,0,1,0,32,1,0,26,0,0,1
0,1,0,0,1,0,50,1,0,106.425,1,0,0
0,1,0,0,1,0,64,0,0,26,0,0,1
1,0,1,0,0,1,19,1,0,26,0,0,1
1,0,1,0,1,0,29.69911764705882,0,0,13.8625,1,0,0
0,0,0,1,1,0,33,1,1,20.525,0,0,1
1,0,1,0,1,0,8,1,1,36.75,0,0,1
1,1,0,0,1,0,17,0,2,110.8833,1,0,0
0,0,1,0,1,0,27,0,0,26,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8292,0,1,0
1,0,0,1,1,0,22,0,0,7.225,1,0,0
1,0,0,1,0,1,22,0,0,7.775,0,0,1
0,1,0,0,1,0,62,0,0,26.55,0,0,1
1,1,0,0,0,1,48,1,0,39.6,1,0,0
0,1,0,0,1,0,29.69911764705882,0,0,227.525,1,0,0
1,1,0,0,0,1,39,1,1,79.65,0,0,1
1,0,0,1,0,1,36,1,0,17.4,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.75,0,1,0
0,0,0,1,1,0,40,0,0,7.8958,0,0,1
0,0,1,0,1,0,28,0,0,13.5,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,8.05,0,0,1
0,0,0,1,0,1,29.69911764705882,0,0,8.05,0,0,1
0,0,0,1,1,0,24,2,0,24.15,0,0,1
0,0,0,1,1,0,19,0,0,7.8958,0,0,1
0,0,0,1,0,1,29,0,4,21.075,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.2292,1,0,0
1,0,0,1,1,0,32,0,0,7.8542,0,0,1
1,0,1,0,1,0,62,0,0,10.5,0,0,1
1,1,0,0,0,1,53,2,0,51.4792,0,0,1
1,1,0,0,1,0,36,0,0,26.3875,0,0,1
1,0,0,1,0,1,29.69911764705882,0,0,7.75,0,1,0
0,0,0,1,1,0,16,0,0,8.05,0,0,1
0,0,0,1,1,0,19,0,0,14.5,0,0,1
1,0,1,0,0,1,34,0,0,13,0,0,1
1,1,0,0,0,1,39,1,0,55.9,0,0,1
0,0,0,1,0,1,29.69911764705882,1,0,14.4583,1,0,0
1,0,0,1,1,0,32,0,0,7.925,0,0,1
1,0,1,0,0,1,25,1,1,30,0,0,1
1,1,0,0,0,1,39,1,1,110.8833,1,0,0
0,0,1,0,1,0,54,0,0,26,0,0,1
0,1,0,0,1,0,36,0,0,40.125,1,0,0
0,0,0,1,1,0,29.69911764705882,0,0,8.7125,1,0,0
1,1,0,0,0,1,18,0,2,79.65,0,0,1
0,0,1,0,1,0,47,0,0,15,0,0,1
1,1,0,0,1,0,60,1,1,79.2,1,0,0
0,0,0,1,1,0,22,0,0,8.05,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,8.05,0,0,1
0,0,0,1,1,0,35,0,0,7.125,0,0,1
1,1,0,0,0,1,52,1,0,78.2667,1,0,0
0,0,0,1,1,0,47,0,0,7.25,0,0,1
0,0,0,1,0,1,29.69911764705882,0,2,7.75,0,1,0
0,0,1,0,1,0,37,1,0,26,0,0,1
0,0,0,1,1,0,36,1,1,24.15,0,0,1
1,0,1,0,0,1,29.69911764705882,0,0,33,0,0,1
0,0,0,1,1,0,49,0,0,0,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.225,1,0,0
1,1,0,0,1,0,49,1,0,56.9292,1,0,0
1,0,1,0,0,1,24,2,1,27,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,0,0,1
0,1,0,0,1,0,29.69911764705882,0,0,42.4,0,0,1
0,0,0,1,1,0,44,0,0,8.05,0,0,1
1,1,0,0,1,0,35,0,0,26.55,1,0,0
0,0,0,1,1,0,36,1,0,15.55,0,0,1
0,0,0,1,1,0,30,0,0,7.8958,0,0,1
1,1,0,0,1,0,27,0,0,30.5,0,0,1
1,0,1,0,0,1,22,1,2,41.5792,1,0,0
1,1,0,0,0,1,40,0,0,153.4625,0,0,1
0,0,0,1,0,1,39,1,5,31.275,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.05,0,0,1
1,0,0,1,0,1,29.69911764705882,1,0,15.5,0,1,0
0,0,0,1,1,0,29.69911764705882,0,0,7.75,0,1,0
0,0,0,1,1,0,35,0,0,8.05,0,0,1
1,0,1,0,0,1,24,1,2,65,0,0,1
0,0,0,1,1,0,34,1,1,14.4,0,0,1
0,0,0,1,0,1,26,1,0,16.1,0,0,1
1,0,1,0,0,1,4,2,1,39,0,0,1
0,0,1,0,1,0,26,0,0,10.5,0,0,1
0,0,0,1,1,0,27,1,0,14.4542,1,0,0
1,1,0,0,1,0,42,1,0,52.5542,0,0,1
1,0,0,1,1,0,20,1,1,15.7417,1,0,0
0,0,0,1,1,0,21,0,0,7.8542,0,0,1
0,0,0,1,1,0,21,0,0,16.1,0,0,1
0,1,0,0,1,0,61,0,0,32.3208,0,0,1
0,0,1,0,1,0,57,0,0,12.35,0,1,0
1,1,0,0,0,1,21,0,0,77.9583,0,0,1
0,0,0,1,1,0,26,0,0,7.8958,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.7333,0,1,0
1,1,0,0,1,0,80,0,0,30,0,0,1
0,0,0,1,1,0,51,0,0,7.0542,0,0,1
1,1,0,0,1,0,32,0,0,30.5,1,0,0
0,1,0,0,1,0,29.69911764705882,0,0,0,0,0,1
0,0,0,1,0,1,9,3,2,27.9,0,0,1
1,0,1,0,0,1,28,0,0,13,0,0,1
0,0,0,1,1,0,32,0,0,7.925,0,0,1
0,0,1,0,1,0,31,1,1,26.25,0,0,1
0,0,0,1,0,1,41,0,5,39.6875,0,0,1
0,0,0,1,1,0,29.69911764705882,1,0,16.1,0,0,1
0,0,0,1,1,0,20,0,0,7.8542,0,0,1
1,1,0,0,0,1,24,0,0,69.3,1,0,0
0,0,0,1,0,1,2,3,2,27.9,0,0,1
1,0,0,1,1,0,29.69911764705882,0,0,56.4958,0,0,1
1,0,0,1,0,1,0.75,2,1,19.2583,1,0,0
1,1,0,0,1,0,48,1,0,76.7292,1,0,0
0,0,0,1,1,0,19,0,0,7.8958,0,0,1
1,1,0,0,1,0,56,0,0,35.5,1,0,0
0,0,0,1,1,0,29.69911764705882,0,0,7.55,0,0,1
1,0,0,1,0,1,23,0,0,7.55,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,0,0,1
1,0,1,0,0,1,18,0,1,23,0,0,1
0,0,0,1,1,0,21,0,0,8.4333,0,0,1
1,0,0,1,0,1,29.69911764705882,0,0,7.8292,0,1,0
0,0,0,1,0,1,18,0,0,6.75,0,1,0
0,0,1,0,1,0,24,2,0,73.5,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,0,0,1
0,0,0,1,0,1,32,1,1,15.5,0,1,0
0,0,1,0,1,0,23,0,0,13,0,0,1
0,1,0,0,1,0,58,0,2,113.275,1,0,0
1,1,0,0,1,0,50,2,0,133.65,0,0,1
0,0,0,1,1,0,40,0,0,7.225,1,0,0
0,1,0,0,1,0,47,0,0,25.5875,0,0,1
0,0,0,1,1,0,36,0,0,7.4958,0,0,1
1,0,0,1,1,0,20,1,0,7.925,0,0,1
0,0,1,0,1,0,32,2,0,73.5,0,0,1
0,0,1,0,1,0,25,0,0,13,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.775,0,0,1
0,0,0,1,1,0,43,0,0,8.05,0,0,1
1,1,0,0,0,1,29.69911764705882,1,0,52,0,0,1
1,0,1,0,0,1,40,1,1,39,0,0,1
0,1,0,0,1,0,31,1,0,52,0,0,1
0,0,1,0,1,0,70,0,0,10.5,0,0,1
1,0,1,0,1,0,31,0,0,13,0,0,1
0,0,1,0,1,0,29.69911764705882,0,0,0,0,0,1
0,0,0,1,1,0,18,0,0,7.775,0,0,1
0,0,0,1,1,0,24.5,0,0,8.05,0,0,1
1,0,0,1,0,1,18,0,0,9.8417,0,0,1
0,0,0,1,0,1,43,1,6,46.9,0,0,1
1,1,0,0,1,0,36,0,1,512.3292,1,0,0
0,0,0,1,0,1,29.69911764705882,0,0,8.1375,0,1,0
1,1,0,0,1,0,27,0,0,76.7292,1,0,0
0,0,0,1,1,0,20,0,0,9.225,0,0,1
0,0,0,1,1,0,14,5,2,46.9,0,0,1
0,0,1,0,1,0,60,1,1,39,0,0,1
0,0,1,0,1,0,25,1,2,41.5792,1,0,0
0,0,0,1,1,0,14,4,1,39.6875,0,0,1
0,0,0,1,1,0,19,0,0,10.1708,0,0,1
0,0,0,1,1,0,18,0,0,7.7958,0,0,1
1,1,0,0,0,1,15,0,1,211.3375,0,0,1
1,1,0,0,1,0,31,1,0,57,0,0,1
1,0,0,1,0,1,4,0,1,13.4167,1,0,0
1,0,0,1,1,0,29.69911764705882,0,0,56.4958,0,0,1
0,0,0,1,1,0,25,0,0,7.225,1,0,0
0,1,0,0,1,0,60,0,0,26.55,0,0,1
0,0,1,0,1,0,52,0,0,13.5,0,0,1
0,0,0,1,1,0,44,0,0,8.05,0,0,1
1,0,0,1,0,1,29.69911764705882,0,0,7.7333,0,1,0
0,1,0,0,1,0,49,1,1,110.8833,1,0,0
0,0,0,1,1,0,42,0,0,7.65,0,0,1
1,1,0,0,0,1,18,1,0,227.525,1,0,0
1,1,0,0,1,0,35,0,0,26.2875,0,0,1
0,0,0,1,0,1,18,0,1,14.4542,1,0,0
0,0,0,1,1,0,25,0,0,7.7417,0,1,0
0,0,0,1,1,0,26,1,0,7.8542,0,0,1
0,0,1,0,1,0,39,0,0,26,0,0,1
1,0,1,0,0,1,45,0,0,13.5,0,0,1
1,1,0,0,1,0,42,0,0,26.2875,0,0,1
1,1,0,0,0,1,22,0,0,151.55,0,0,1
1,0,0,1,1,0,29.69911764705882,1,1,15.2458,1,0,0
1,1,0,0,0,1,24,0,0,49.5042,1,0,0
0,1,0,0,1,0,29.69911764705882,0,0,26.55,0,0,1
1,1,0,0,1,0,48,1,0,52,0,0,1
0,0,0,1,1,0,29,0,0,9.4833,0,0,1
0,0,1,0,1,0,52,0,0,13,0,0,1
0,0,0,1,1,0,19,0,0,7.65,0,0,1
1,1,0,0,0,1,38,0,0,227.525,1,0,0
1,0,1,0,0,1,27,0,0,10.5,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,15.5,0,1,0
0,0,0,1,1,0,33,0,0,7.775,0,0,1
1,0,1,0,0,1,6,0,1,33,0,0,1
0,0,0,1,1,0,17,1,0,7.0542,0,0,1
0,0,1,0,1,0,34,0,0,13,0,0,1
0,0,1,0,1,0,50,0,0,13,0,0,1
1,1,0,0,1,0,27,1,0,53.1,0,0,1
0,0,0,1,1,0,20,0,0,8.6625,0,0,1
1,0,1,0,0,1,30,3,0,21,0,0,1
1,0,0,1,0,1,29.69911764705882,0,0,7.7375,0,1,0
0,0,1,0,1,0,25,1,0,26,0,0,1
0,0,0,1,0,1,25,1,0,7.925,0,0,1
1,1,0,0,0,1,29,0,0,211.3375,0,0,1
0,0,0,1,1,0,11,0,0,18.7875,1,0,0
0,0,1,0,1,0,29.69911764705882,0,0,0,0,0,1
0,0,1,0,1,0,23,0,0,13,0,0,1
0,0,1,0,1,0,23,0,0,13,0,0,1
0,0,0,1,1,0,28.5,0,0,16.1,0,0,1
0,0,0,1,0,1,48,1,3,34.375,0,0,1
1,1,0,0,1,0,35,0,0,512.3292,1,0,0
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,0,0,1
1,1,0,0,1,0,29.69911764705882,0,0,30,0,0,1
0,1,0,0,1,0,36,1,0,78.85,0,0,1
1,1,0,0,0,1,21,2,2,262.375,1,0,0
0,0,0,1,1,0,24,1,0,16.1,0,0,1
1,0,0,1,1,0,31,0,0,7.925,0,0,1
0,1,0,0,1,0,70,1,1,71,0,0,1
0,0,0,1,1,0,16,1,1,20.25,0,0,1
1,0,1,0,0,1,30,0,0,13,0,0,1
0,1,0,0,1,0,19,1,0,53.1,0,0,1
0,0,0,1,1,0,31,0,0,7.75,0,1,0
1,0,1,0,0,1,4,1,1,23,0,0,1
1,0,0,1,1,0,6,0,1,12.475,0,0,1
0,0,0,1,1,0,33,0,0,9.5,0,0,1
0,0,0,1,1,0,23,0,0,7.8958,0,0,1
1,0,1,0,0,1,48,1,2,65,0,0,1
1,0,1,0,1,0,0.67,1,1,14.5,0,0,1
0,0,0,1,1,0,28,0,0,7.7958,0,0,1
0,0,1,0,1,0,18,0,0,11.5,0,0,1
0,0,0,1,1,0,34,0,0,8.05,0,0,1
1,1,0,0,0,1,33,0,0,86.5,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,14.5,0,0,1
0,0,0,1,1,0,41,0,0,7.125,0,0,1
1,0,0,1,1,0,20,0,0,7.2292,1,0,0
1,1,0,0,0,1,36,1,2,120,0,0,1
0,0,0,1,1,0,16,0,0,7.775,0,0,1
1,1,0,0,0,1,51,1,0,77.9583,0,0,1
0,1,0,0,1,0,29.69911764705882,0,0,39.6,1,0,0
0,0,0,1,0,1,30.5,0,0,7.75,0,1,0
0,0,0,1,1,0,29.69911764705882,1,0,24.15,0,1,0
0,0,0,1,1,0,32,0,0,8.3625,0,0,1
0,0,0,1,1,0,24,0,0,9.5,0,0,1
0,0,0,1,1,0,48,0,0,7.8542,0,0,1
0,0,1,0,0,1,57,0,0,10.5,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.225,1,0,0
1,0,1,0,0,1,54,1,3,23,0,0,1
0,0,0,1,1,0,18,0,0,7.75,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.75,0,1,0
1,0,0,1,0,1,5,0,0,12.475,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.7375,0,1,0
1,1,0,0,0,1,43,0,1,211.3375,0,0,1
1,0,0,1,0,1,13,0,0,7.2292,1,0,0
1,1,0,0,0,1,17,1,0,57,0,0,1
0,1,0,0,1,0,29,0,0,30,0,0,1
0,0,0,1,1,0,29.69911764705882,1,2,23.45,0,0,1
0,0,0,1,1,0,25,0,0,7.05,0,0,1
0,0,0,1,1,0,25,0,0,7.25,0,0,1
1,0,0,1,0,1,18,0,0,7.4958,0,0,1
0,0,0,1,1,0,8,4,1,29.125,0,1,0
1,0,0,1,1,0,1,1,2,20.575,0,0,1
0,1,0,0,1,0,46,0,0,79.2,1,0,0
0,0,0,1,1,0,29.69911764705882,0,0,7.75,0,1,0
0,0,1,0,1,0,16,0,0,26,0,0,1
0,0,0,1,0,1,29.69911764705882,8,2,69.55,0,0,1
0,1,0,0,1,0,29.69911764705882,0,0,30.6958,1,0,0
0,0,0,1,1,0,25,0,0,7.8958,0,0,1
0,0,1,0,1,0,39,0,0,13,0,0,1
1,1,0,0,0,1,49,0,0,25.9292,0,0,1
1,0,0,1,0,1,31,0,0,8.6833,0,0,1
0,0,0,1,1,0,30,0,0,7.2292,1,0,0
0,0,0,1,0,1,30,1,1,24.15,0,0,1
0,0,1,0,1,0,34,0,0,13,0,0,1
1,0,1,0,0,1,31,1,1,26.25,0,0,1
1,1,0,0,1,0,11,1,2,120,0,0,1
1,0,0,1,1,0,0.42,0,1,8.5167,1,0,0
1,0,0,1,1,0,27,0,0,6.975,0,0,1
0,0,0,1,1,0,31,0,0,7.775,0,0,1
0,1,0,0,1,0,39,0,0,0,0,0,1
0,0,0,1,0,1,18,0,0,7.775,0,0,1
0,0,1,0,1,0,39,0,0,13,0,0,1
1,1,0,0,0,1,33,1,0,53.1,0,0,1
0,0,0,1,1,0,26,0,0,7.8875,0,0,1
0,0,0,1,1,0,39,0,0,24.15,0,0,1
0,0,1,0,1,0,35,0,0,10.5,0,0,1
0,0,0,1,0,1,6,4,2,31.275,0,0,1
0,0,0,1,1,0,30.5,0,0,8.05,0,0,1
0,1,0,0,1,0,29.69911764705882,0,0,0,0,0,1
0,0,0,1,0,1,23,0,0,7.925,0,0,1
0,0,1,0,1,0,31,1,1,37.0042,1,0,0
0,0,0,1,1,0,43,0,0,6.45,0,0,1
0,0,0,1,1,0,10,3,2,27.9,0,0,1
1,1,0,0,0,1,52,1,1,93.5,0,0,1
1,0,0,1,1,0,27,0,0,8.6625,0,0,1
0,1,0,0,1,0,38,0,0,0,0,0,1
1,0,0,1,0,1,27,0,1,12.475,0,0,1
0,0,0,1,1,0,2,4,1,39.6875,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,6.95,0,1,0
0,0,0,1,1,0,29.69911764705882,0,0,56.4958,0,0,1
1,0,1,0,1,0,1,0,2,37.0042,1,0,0
1,0,0,1,1,0,29.69911764705882,0,0,7.75,0,1,0
1,1,0,0,0,1,62,0,0,80,0,0,1
1,0,0,1,0,1,15,1,0,14.4542,1,0,0
1,0,1,0,1,0,0.83,1,1,18.75,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.2292,1,0,0
0,0,0,1,1,0,23,0,0,7.8542,0,0,1
0,0,0,1,1,0,18,0,0,8.3,0,0,1
1,1,0,0,0,1,39,1,1,83.1583,1,0,0
0,0,0,1,1,0,21,0,0,8.6625,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,8.05,0,0,1
1,0,0,1,1,0,32,0,0,56.4958,0,0,1
1,1,0,0,1,0,29.69911764705882,0,0,29.7,1,0,0
0,0,0,1,1,0,20,0,0,7.925,0,0,1
0,0,1,0,1,0,16,0,0,10.5,0,0,1
1,1,0,0,0,1,30,0,0,31,1,0,0
0,0,0,1,1,0,34.5,0,0,6.4375,1,0,0
0,0,0,1,1,0,17,0,0,8.6625,0,0,1
0,0,0,1,1,0,42,0,0,7.55,0,0,1
0,0,0,1,1,0,29.69911764705882,8,2,69.55,0,0,1
0,0,0,1,1,0,35,0,0,7.8958,1,0,0
0,0,1,0,1,0,28,0,1,33,0,0,1
1,1,0,0,0,1,29.69911764705882,1,0,89.1042,1,0,0
0,0,0,1,1,0,4,4,2,31.275,0,0,1
0,0,0,1,1,0,74,0,0,7.775,0,0,1
0,0,0,1,0,1,9,1,1,15.2458,1,0,0
1,1,0,0,0,1,16,0,1,39.4,0,0,1
0,0,1,0,0,1,44,1,0,26,0,0,1
1,0,0,1,0,1,18,0,1,9.35,0,0,1
1,1,0,0,0,1,45,1,1,164.8667,0,0,1
1,1,0,0,1,0,51,0,0,26.55,0,0,1
1,0,0,1,0,1,24,0,3,19.2583,1,0,0
0,0,0,1,1,0,29.69911764705882,0,0,7.2292,1,0,0
0,0,0,1,1,0,41,2,0,14.1083,0,0,1
0,0,1,0,1,0,21,1,0,11.5,0,0,1
1,1,0,0,0,1,48,0,0,25.9292,0,0,1
0,0,0,1,0,1,29.69911764705882,8,2,69.55,0,0,1
0,0,1,0,1,0,24,0,0,13,0,0,1
1,0,1,0,0,1,42,0,0,13,0,0,1
1,0,1,0,0,1,27,1,0,13.8583,1,0,0
0,1,0,0,1,0,31,0,0,50.4958,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,9.5,0,0,1
1,0,0,1,1,0,4,1,1,11.1333,0,0,1
0,0,0,1,1,0,26,0,0,7.8958,0,0,1
1,1,0,0,0,1,47,1,1,52.5542,0,0,1
0,1,0,0,1,0,33,0,0,5,0,0,1
0,0,0,1,1,0,47,0,0,9,0,0,1
1,0,1,0,0,1,28,1,0,24,1,0,0
1,0,0,1,0,1,15,0,0,7.225,1,0,0
0,0,0,1,1,0,20,0,0,9.8458,0,0,1
0,0,0,1,1,0,19,0,0,7.8958,0,0,1
0,0,0,1,1,0,29.69911764705882,0,0,7.8958,0,0,1
1,1,0,0,0,1,56,0,1,83.1583,1,0,0
1,0,1,0,0,1,25,0,1,26,0,0,1
0,0,0,1,1,0,33,0,0,7.8958,0,0,1
0,0,0,1,0,1,22,0,0,10.5167,0,0,1
0,0,1,0,1,0,28,0,0,10.5,0,0,1
0,0,0,1,1,0,25,0,0,7.05,0,0,1
0,0,0,1,0,1,39,0,5,29.125,0,1,0
0,0,1,0,1,0,27,0,0,13,0,0,1
1,1,0,0,0,1,19,0,0,30,0,0,1
0,0,0,1,0,1,29.69911764705882,1,2,23.45,0,0,1
1,1,0,0,1,0,26,0,0,30,1,0,0
0,0,0,1,1,0,32,0,0,7.75,0,1,0

Log output

/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/bin/java -Didea.launcher.port=7532 "-Didea.launcher.bin.path=/Applications/IntelliJ IDEA CE.app/Contents/bin" -Dfile.encoding=UTF-8 -classpath "/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/charsets.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/deploy.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/ext/cldrdata.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/ext/dnsns.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/ext/jfxrt.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/ext/localedata.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/ext/nashorn.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/ext/sunec.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/ext/sunjce_provider.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/ext/sunpkcs11.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/ext/zipfs.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/javaws.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/jce.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/jfr.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/jfxswt.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/jsse.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/management-agent.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/plugin.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/resources.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/jre/lib/rt.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/lib/ant-javafx.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/lib/dt.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/lib/javafx-mx.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/lib/jconsole.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/lib/sa-jdi.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_25.jdk/Contents/Home/lib/tools.jar:/Users/danlin/git/dl4j-lab/dl4j/target/classes:/Users/danlin/.m2/repository/org/nd4j/nd4j-native-platform/0.5.0/nd4j-native-platform-0.5.0.jar:/Users/danlin/.m2/repository/org/nd4j/nd4j-native/0.5.0/nd4j-native-0.5.0.jar:/Users/danlin/.m2/repository/org/nd4j/nd4j-native-api/0.5.0/nd4j-native-api-0.5.0.jar:/Users/danlin/.m2/repository/org/nd4j/nd4j-native/0.5.0/nd4j-native-0.5.0-macosx-x86_64.jar:/Users/danlin/.m2/repository/org/nd4j/nd4j-native/0.5.0/nd4j-native-0.5.0-linux-x86_64.jar:/Users/danlin/.m2/repository/org/nd4j/nd4j-native/0.5.0/nd4j-native-0.5.0-windows-x86_64.jar:/Users/danlin/.m2/repository/org/nd4j/nd4j-native/0.5.0/nd4j-native-0.5.0-linux-ppc64le.jar:/Users/danlin/.m2/repository/org/deeplearning4j/deeplearning4j-core/0.5.0/deeplearning4j-core-0.5.0.jar:/Users/danlin/.m2/repository/org/slf4j/slf4j-api/1.7.12/slf4j-api-1.7.12.jar:/Users/danlin/.m2/repository/ch/qos/logback/logback-classic/1.1.2/logback-classic-1.1.2.jar:/Users/danlin/.m2/repository/ch/qos/logback/logback-core/1.1.2/logback-core-1.1.2.jar:/Users/danlin/.m2/repository/org/apache/commons/commons-math3/3.4.1/commons-math3-3.4.1.jar:/Users/danlin/.m2/repository/commons-io/commons-io/2.4/commons-io-2.4.jar:/Users/danlin/.m2/repository/org/apache/commons/commons-compress/1.8/commons-compress-1.8.jar:/Users/danlin/.m2/repository/org/tukaani/xz/1.5/xz-1.5.jar:/Users/danlin/.m2/repository/org/nd4j/nd4j-api/0.5.0/nd4j-api-0.5.0.jar:/Users/danlin/.m2/repository/org/nd4j/nd4j-buffer/0.5.0/nd4j-buffer-0.5.0.jar:/Users/danlin/.m2/repository/org/nd4j/nd4j-common/0.5.0/nd4j-common-0.5.0.jar:/Users/danlin/.m2/repository/org/reflections/reflections/0.9.10/reflections-0.9.10.jar:/Users/danlin/.m2/repository/com/google/code/findbugs/annotations/2.0.1/annotations-2.0.1.jar:/Users/danlin/.m2/repository/org/nd4j/nd4j-context/0.5.0/nd4j-context-0.5.0.jar:/Users/danlin/.m2/repository/org/apache/commons/commons-lang3/3.3.1/commons-lang3-3.3.1.jar:/Users/danlin/.m2/repository/com/fasterxml/jackson/core/jackson-core/2.5.1/jackson-core-2.5.1.jar:/Users/danlin/.m2/repository/com/fasterxml/jackson/core/jackson-databind/2.5.1/jackson-databind-2.5.1.jar:/Users/danlin/.m2/repository/org/json/json/20131018/json-20131018.jar:/Users/danlin/.m2/repository/com/fasterxml/jackson/core/jackson-annotations/2.5.1/jackson-annotations-2.5.1.jar:/Users/danlin/.m2/repository/org/projectlombok/lombok/1.16.4/lombok-1.16.4.jar:/Users/danlin/.m2/repository/com/fasterxml/jackson/dataformat/jackson-dataformat-yaml/2.5.1/jackson-dataformat-yaml-2.5.1.jar:/Users/danlin/.m2/repository/org/yaml/snakeyaml/1.12/snakeyaml-1.12.jar:/Users/danlin/.m2/repository/org/datavec/datavec-nd4j-common/0.5.0/datavec-nd4j-common-0.5.0.jar:/Users/danlin/.m2/repository/org/datavec/datavec-api/0.5.0/datavec-api-0.5.0.jar:/Users/danlin/.m2/repository/com/fasterxml/jackson/datatype/jackson-datatype-joda/2.4.4/jackson-datatype-joda-2.4.4.jar:/Users/danlin/.m2/repository/joda-time/joda-time/2.9.2/joda-time-2.9.2.jar:/Users/danlin/.m2/repository/org/freemarker/freemarker/2.3.23/freemarker-2.3.23.jar:/Users/danlin/.m2/repository/org/datavec/datavec-data-image/0.5.0/datavec-data-image-0.5.0.jar:/Users/danlin/.m2/repository/com/github/jai-imageio/jai-imageio-core/1.3.0/jai-imageio-core-1.3.0.jar:/Users/danlin/.m2/repository/com/twelvemonkeys/imageio/imageio-jpeg/3.1.1/imageio-jpeg-3.1.1.jar:/Users/danlin/.m2/repository/com/twelvemonkeys/imageio/imageio-core/3.1.1/imageio-core-3.1.1.jar:/Users/danlin/.m2/repository/com/twelvemonkeys/imageio/imageio-metadata/3.1.1/imageio-metadata-3.1.1.jar:/Users/danlin/.m2/repository/com/twelvemonkeys/common/common-lang/3.1.1/common-lang-3.1.1.jar:/Users/danlin/.m2/repository/com/twelvemonkeys/common/common-io/3.1.1/common-io-3.1.1.jar:/Users/danlin/.m2/repository/com/twelvemonkeys/common/common-image/3.1.1/common-image-3.1.1.jar:/Users/danlin/.m2/repository/com/twelvemonkeys/imageio/imageio-tiff/3.1.1/imageio-tiff-3.1.1.jar:/Users/danlin/.m2/repository/com/twelvemonkeys/imageio/imageio-psd/3.1.1/imageio-psd-3.1.1.jar:/Users/danlin/.m2/repository/com/twelvemonkeys/imageio/imageio-bmp/3.1.1/imageio-bmp-3.1.1.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp/1.2.3/javacpp-1.2.3.jar:/Users/danlin/.m2/repository/org/bytedeco/javacv/1.2/javacv-1.2.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/opencv/3.1.0-1.2/opencv-3.1.0-1.2.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/opencv/3.1.0-1.2/opencv-3.1.0-1.2-linux-x86_64.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/opencv/3.1.0-1.2/opencv-3.1.0-1.2-macosx-x86_64.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/opencv/3.1.0-1.2/opencv-3.1.0-1.2-windows-x86_64.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/opencv/3.1.0-1.2/opencv-3.1.0-1.2-linux-ppc64le.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/ffmpeg/3.0.2-1.2/ffmpeg-3.0.2-1.2.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/ffmpeg/3.0.2-1.2/ffmpeg-3.0.2-1.2-linux-x86_64.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/ffmpeg/3.0.2-1.2/ffmpeg-3.0.2-1.2-macosx-x86_64.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/ffmpeg/3.0.2-1.2/ffmpeg-3.0.2-1.2-windows-x86_64.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/ffmpeg/3.0.2-1.2/ffmpeg-3.0.2-1.2-linux-ppc64le.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/leptonica/1.73-1.2/leptonica-1.73-1.2.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/leptonica/1.73-1.2/leptonica-1.73-1.2-linux-x86_64.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/leptonica/1.73-1.2/leptonica-1.73-1.2-macosx-x86_64.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/leptonica/1.73-1.2/leptonica-1.73-1.2-windows-x86_64.jar:/Users/danlin/.m2/repository/org/bytedeco/javacpp-presets/leptonica/1.73-1.2/leptonica-1.73-1.2-linux-ppc64le.jar:/Users/danlin/.m2/repository/org/deeplearning4j/deeplearning4j-nlp/0.5.0/deeplearning4j-nlp-0.5.0.jar:/Users/danlin/.m2/repository/org/apache/directory/studio/org.apache.commons.codec/1.8/org.apache.commons.codec-1.8.jar:/Users/danlin/.m2/repository/commons-codec/commons-codec/1.8/commons-codec-1.8.jar:/Users/danlin/.m2/repository/it/unimi/dsi/dsiutils/2.2.2/dsiutils-2.2.2.jar:/Users/danlin/.m2/repository/it/unimi/dsi/fastutil/6.5.15/fastutil-6.5.15.jar:/Users/danlin/.m2/repository/com/martiansoftware/jsap/2.1/jsap-2.1.jar:/Users/danlin/.m2/repository/commons-configuration/commons-configuration/1.8/commons-configuration-1.8.jar:/Users/danlin/.m2/repository/commons-lang/commons-lang/2.6/commons-lang-2.6.jar:/Users/danlin/.m2/repository/commons-logging/commons-logging/1.1.1/commons-logging-1.1.1.jar:/Users/danlin/.m2/repository/commons-collections/commons-collections/20040616/commons-collections-20040616.jar:/Users/danlin/.m2/repository/org/cleartk/cleartk-snowball/2.0.0/cleartk-snowball-2.0.0.jar:/Users/danlin/.m2/repository/org/apache/lucene/lucene-snowball/3.0.3/lucene-snowball-3.0.3.jar:/Users/danlin/.m2/repository/org/cleartk/cleartk-util/2.0.0/cleartk-util-2.0.0.jar:/Users/danlin/.m2/repository/org/apache/uima/uimaj-core/2.5.0/uimaj-core-2.5.0.jar:/Users/danlin/.m2/repository/org/apache/uima/uimafit-core/2.0.0/uimafit-core-2.0.0.jar:/Users/danlin/.m2/repository/commons-logging/commons-logging-api/1.1/commons-logging-api-1.1.jar:/Users/danlin/.m2/repository/org/springframework/spring-core/3.1.2.RELEASE/spring-core-3.1.2.RELEASE.jar:/Users/danlin/.m2/repository/org/springframework/spring-asm/3.1.2.RELEASE/spring-asm-3.1.2.RELEASE.jar:/Users/danlin/.m2/repository/org/springframework/spring-context/3.1.2.RELEASE/spring-context-3.1.2.RELEASE.jar:/Users/danlin/.m2/repository/org/springframework/spring-aop/3.1.2.RELEASE/spring-aop-3.1.2.RELEASE.jar:/Users/danlin/.m2/repository/aopalliance/aopalliance/1.0/aopalliance-1.0.jar:/Users/danlin/.m2/repository/org/springframework/spring-expression/3.1.2.RELEASE/spring-expression-3.1.2.RELEASE.jar:/Users/danlin/.m2/repository/org/springframework/spring-beans/3.1.2.RELEASE/spring-beans-3.1.2.RELEASE.jar:/Users/danlin/.m2/repository/org/cleartk/cleartk-type-system/2.0.0/cleartk-type-system-2.0.0.jar:/Users/danlin/.m2/repository/org/cleartk/cleartk-opennlp-tools/2.0.0/cleartk-opennlp-tools-2.0.0.jar:/Users/danlin/.m2/repository/org/apache/opennlp/opennlp-maxent/3.0.3/opennlp-maxent-3.0.3.jar:/Users/danlin/.m2/repository/org/apache/opennlp/opennlp-tools/1.5.3/opennlp-tools-1.5.3.jar:/Users/danlin/.m2/repository/net/sf/jwordnet/jwnl/1.3.3/jwnl-1.3.3.jar:/Users/danlin/.m2/repository/org/apache/opennlp/opennlp-uima/1.5.3/opennlp-uima-1.5.3.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-assets/0.8.0/dropwizard-assets-0.8.0.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-core/0.8.0/dropwizard-core-0.8.0.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-util/0.8.0/dropwizard-util-0.8.0.jar:/Users/danlin/.m2/repository/com/google/code/findbugs/jsr305/3.0.0/jsr305-3.0.0.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-jackson/0.8.0/dropwizard-jackson-0.8.0.jar:/Users/danlin/.m2/repository/com/fasterxml/jackson/datatype/jackson-datatype-jdk7/2.5.1/jackson-datatype-jdk7-2.5.1.jar:/Users/danlin/.m2/repository/com/fasterxml/jackson/datatype/jackson-datatype-guava/2.5.1/jackson-datatype-guava-2.5.1.jar:/Users/danlin/.m2/repository/com/fasterxml/jackson/module/jackson-module-afterburner/2.5.1/jackson-module-afterburner-2.5.1.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-validation/0.8.0/dropwizard-validation-0.8.0.jar:/Users/danlin/.m2/repository/org/hibernate/hibernate-validator/5.1.3.Final/hibernate-validator-5.1.3.Final.jar:/Users/danlin/.m2/repository/javax/validation/validation-api/1.1.0.Final/validation-api-1.1.0.Final.jar:/Users/danlin/.m2/repository/org/jboss/logging/jboss-logging/3.1.3.GA/jboss-logging-3.1.3.GA.jar:/Users/danlin/.m2/repository/com/fasterxml/classmate/1.0.0/classmate-1.0.0.jar:/Users/danlin/.m2/repository/org/glassfish/javax.el/3.0.0/javax.el-3.0.0.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-configuration/0.8.0/dropwizard-configuration-0.8.0.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-logging/0.8.0/dropwizard-logging-0.8.0.jar:/Users/danlin/.m2/repository/io/dropwizard/metrics/metrics-logback/3.1.0/metrics-logback-3.1.0.jar:/Users/danlin/.m2/repository/org/slf4j/jul-to-slf4j/1.7.10/jul-to-slf4j-1.7.10.jar:/Users/danlin/.m2/repository/org/slf4j/log4j-over-slf4j/1.7.10/log4j-over-slf4j-1.7.10.jar:/Users/danlin/.m2/repository/org/slf4j/jcl-over-slf4j/1.7.10/jcl-over-slf4j-1.7.10.jar:/Users/danlin/.m2/repository/org/eclipse/jetty/jetty-util/9.2.9.v20150224/jetty-util-9.2.9.v20150224.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-metrics/0.8.0/dropwizard-metrics-0.8.0.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-jersey/0.8.0/dropwizard-jersey-0.8.0.jar:/Users/danlin/.m2/repository/org/glassfish/jersey/core/jersey-server/2.16/jersey-server-2.16.jar:/Users/danlin/.m2/repository/org/glassfish/jersey/media/jersey-media-jaxb/2.16/jersey-media-jaxb-2.16.jar:/Users/danlin/.m2/repository/org/glassfish/jersey/ext/jersey-metainf-services/2.16/jersey-metainf-services-2.16.jar:/Users/danlin/.m2/repository/io/dropwizard/metrics/metrics-jersey2/3.1.0/metrics-jersey2-3.1.0.jar:/Users/danlin/.m2/repository/com/fasterxml/jackson/jaxrs/jackson-jaxrs-json-provider/2.5.1/jackson-jaxrs-json-provider-2.5.1.jar:/Users/danlin/.m2/repository/com/fasterxml/jackson/jaxrs/jackson-jaxrs-base/2.5.1/jackson-jaxrs-base-2.5.1.jar:/Users/danlin/.m2/repository/com/fasterxml/jackson/module/jackson-module-jaxb-annotations/2.5.1/jackson-module-jaxb-annotations-2.5.1.jar:/Users/danlin/.m2/repository/org/glassfish/jersey/containers/jersey-container-servlet/2.16/jersey-container-servlet-2.16.jar:/Users/danlin/.m2/repository/org/glassfish/jersey/containers/jersey-container-servlet-core/2.16/jersey-container-servlet-core-2.16.jar:/Users/danlin/.m2/repository/org/eclipse/jetty/jetty-server/9.2.9.v20150224/jetty-server-9.2.9.v20150224.jar:/Users/danlin/.m2/repository/javax/servlet/javax.servlet-api/3.1.0/javax.servlet-api-3.1.0.jar:/Users/danlin/.m2/repository/org/eclipse/jetty/jetty-io/9.2.9.v20150224/jetty-io-9.2.9.v20150224.jar:/Users/danlin/.m2/repository/org/eclipse/jetty/jetty-webapp/9.2.9.v20150224/jetty-webapp-9.2.9.v20150224.jar:/Users/danlin/.m2/repository/org/eclipse/jetty/jetty-xml/9.2.9.v20150224/jetty-xml-9.2.9.v20150224.jar:/Users/danlin/.m2/repository/org/eclipse/jetty/jetty-continuation/9.2.9.v20150224/jetty-continuation-9.2.9.v20150224.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-jetty/0.8.0/dropwizard-jetty-0.8.0.jar:/Users/danlin/.m2/repository/io/dropwizard/metrics/metrics-jetty9/3.1.0/metrics-jetty9-3.1.0.jar:/Users/danlin/.m2/repository/org/eclipse/jetty/jetty-servlet/9.2.9.v20150224/jetty-servlet-9.2.9.v20150224.jar:/Users/danlin/.m2/repository/org/eclipse/jetty/jetty-security/9.2.9.v20150224/jetty-security-9.2.9.v20150224.jar:/Users/danlin/.m2/repository/org/eclipse/jetty/jetty-servlets/9.2.9.v20150224/jetty-servlets-9.2.9.v20150224.jar:/Users/danlin/.m2/repository/org/eclipse/jetty/jetty-http/9.2.9.v20150224/jetty-http-9.2.9.v20150224.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-lifecycle/0.8.0/dropwizard-lifecycle-0.8.0.jar:/Users/danlin/.m2/repository/io/dropwizard/metrics/metrics-core/3.1.0/metrics-core-3.1.0.jar:/Users/danlin/.m2/repository/io/dropwizard/metrics/metrics-jvm/3.1.0/metrics-jvm-3.1.0.jar:/Users/danlin/.m2/repository/io/dropwizard/metrics/metrics-servlets/3.1.0/metrics-servlets-3.1.0.jar:/Users/danlin/.m2/repository/io/dropwizard/metrics/metrics-json/3.1.0/metrics-json-3.1.0.jar:/Users/danlin/.m2/repository/io/dropwizard/metrics/metrics-healthchecks/3.1.0/metrics-healthchecks-3.1.0.jar:/Users/danlin/.m2/repository/net/sourceforge/argparse4j/argparse4j/0.4.4/argparse4j-0.4.4.jar:/Users/danlin/.m2/repository/org/eclipse/jetty/toolchain/setuid/jetty-setuid-java/1.0.2/jetty-setuid-java-1.0.2.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-servlets/0.8.0/dropwizard-servlets-0.8.0.jar:/Users/danlin/.m2/repository/io/dropwizard/metrics/metrics-annotation/3.1.0/metrics-annotation-3.1.0.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-views-mustache/0.8.0/dropwizard-views-mustache-0.8.0.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-views/0.8.0/dropwizard-views-0.8.0.jar:/Users/danlin/.m2/repository/com/github/spullara/mustache/java/compiler/0.8.17/compiler-0.8.17.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-views-freemarker/0.8.0/dropwizard-views-freemarker-0.8.0.jar:/Users/danlin/.m2/repository/org/nd4j/nd4j-jackson/0.5.0/nd4j-jackson-0.5.0.jar:/Users/danlin/.m2/repository/org/deeplearning4j/deeplearning4j-ui/0.5.0/deeplearning4j-ui-0.5.0.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-client/0.8.0/dropwizard-client-0.8.0.jar:/Users/danlin/.m2/repository/org/glassfish/jersey/core/jersey-client/2.16/jersey-client-2.16.jar:/Users/danlin/.m2/repository/javax/ws/rs/javax.ws.rs-api/2.0.1/javax.ws.rs-api-2.0.1.jar:/Users/danlin/.m2/repository/org/glassfish/hk2/hk2-api/2.4.0-b09/hk2-api-2.4.0-b09.jar:/Users/danlin/.m2/repository/org/glassfish/hk2/hk2-utils/2.4.0-b09/hk2-utils-2.4.0-b09.jar:/Users/danlin/.m2/repository/org/glassfish/hk2/external/aopalliance-repackaged/2.4.0-b09/aopalliance-repackaged-2.4.0-b09.jar:/Users/danlin/.m2/repository/org/glassfish/hk2/external/javax.inject/2.4.0-b09/javax.inject-2.4.0-b09.jar:/Users/danlin/.m2/repository/org/glassfish/hk2/hk2-locator/2.4.0-b09/hk2-locator-2.4.0-b09.jar:/Users/danlin/.m2/repository/org/javassist/javassist/3.18.1-GA/javassist-3.18.1-GA.jar:/Users/danlin/.m2/repository/io/dropwizard/metrics/metrics-httpclient/3.1.0/metrics-httpclient-3.1.0.jar:/Users/danlin/.m2/repository/org/apache/httpcomponents/httpclient/4.3.5/httpclient-4.3.5.jar:/Users/danlin/.m2/repository/org/apache/httpcomponents/httpcore/4.3.2/httpcore-4.3.2.jar:/Users/danlin/.m2/repository/org/glassfish/jersey/connectors/jersey-apache-connector/2.16/jersey-apache-connector-2.16.jar:/Users/danlin/.m2/repository/io/dropwizard/dropwizard-forms/0.8.0/dropwizard-forms-0.8.0.jar:/Users/danlin/.m2/repository/org/glassfish/jersey/media/jersey-media-multipart/2.16/jersey-media-multipart-2.16.jar:/Users/danlin/.m2/repository/org/glassfish/jersey/core/jersey-common/2.16/jersey-common-2.16.jar:/Users/danlin/.m2/repository/javax/annotation/javax.annotation-api/1.2/javax.annotation-api-1.2.jar:/Users/danlin/.m2/repository/org/glassfish/jersey/bundles/repackaged/jersey-guava/2.16/jersey-guava-2.16.jar:/Users/danlin/.m2/repository/org/glassfish/hk2/osgi-resource-locator/1.0.1/osgi-resource-locator-1.0.1.jar:/Users/danlin/.m2/repository/org/jvnet/mimepull/mimepull/1.9.3/mimepull-1.9.3.jar:/Users/danlin/.m2/repository/com/google/guava/guava/19.0/guava-19.0.jar:/Users/danlin/.m2/repository/org/datavec/datavec-data-codec/0.4.0/datavec-data-codec-0.4.0.jar:/Users/danlin/.m2/repository/org/jcodec/jcodec/0.1.5/jcodec-0.1.5.jar:/Users/danlin/.m2/repository/jfree/jfreechart/1.0.13/jfreechart-1.0.13.jar:/Users/danlin/.m2/repository/jfree/jcommon/1.0.16/jcommon-1.0.16.jar:/Users/danlin/.m2/repository/org/deeplearning4j/arbiter-deeplearning4j/0.5.0/arbiter-deeplearning4j-0.5.0.jar:/Users/danlin/.m2/repository/org/deeplearning4j/arbiter-core/0.5.0/arbiter-core-0.5.0.jar:/Users/danlin/.m2/repository/args4j/args4j/2.33/args4j-2.33.jar:/Users/danlin/.m2/repository/org/deeplearning4j/deeplearning4j-ui-components/0.5.0/deeplearning4j-ui-components-0.5.0.jar:/Applications/IntelliJ IDEA CE.app/Contents/lib/idea_rt.jar" com.intellij.rt.execution.application.AppMain kaggle.TitanicOptimization
16/08/07 21:50:29 INFO o.r.Reflections: Reflections took 239 ms to scan 11 urls, producing 111 keys and 368 values 
16/08/07 21:50:30 INFO o.d.a.s.l.m.LocalMultiLayerNetworkSaver: LocalMultiLayerNetworkSaver saving networks to local directory: arbiterExample/
INFO  [2016-08-07 19:50:33,851] org.eclipse.jetty.util.log: Logging initialized @6033ms
INFO  [2016-08-07 19:50:33,913] io.dropwizard.assets.AssetsBundle: Registering AssetBundle with name: assets for path /assets/*
INFO  [2016-08-07 19:50:33,989] io.dropwizard.server.ServerFactory: Starting arbiter-ui
WARN  [2016-08-07 19:50:34,079] org.eclipse.jetty.server.ServerConnector: Acceptors should be <= availableProcessors: ServerConnector@53ac845a{HTTP/1.1}{0.0.0.0:0}
INFO  [2016-08-07 19:50:34,117] org.eclipse.jetty.setuid.SetUIDListener: Opened application@53ac845a{HTTP/1.1}{0.0.0.0:8080}
INFO  [2016-08-07 19:50:34,117] org.eclipse.jetty.setuid.SetUIDListener: Opened admin@3cee53dc{HTTP/1.1}{0.0.0.0:8081}
INFO  [2016-08-07 19:50:34,122] org.eclipse.jetty.server.Server: jetty-9.2.9.v20150224
INFO  [2016-08-07 19:50:35,879] io.dropwizard.jersey.DropwizardResourceConfig: The following paths were found for the configured resources:

    GET     /results (org.deeplearning4j.arbiter.optimize.ui.resources.SummaryResultsResource)
    POST    /results/update (org.deeplearning4j.arbiter.optimize.ui.resources.SummaryResultsResource)
    GET     /config (org.deeplearning4j.arbiter.optimize.ui.resources.ConfigResource)
    POST    /config/update (org.deeplearning4j.arbiter.optimize.ui.resources.ConfigResource)
    GET     /modelResults/lastUpdate (org.deeplearning4j.arbiter.optimize.ui.resources.CandidateResultsResource)
    GET     /modelResults/{id} (org.deeplearning4j.arbiter.optimize.ui.resources.CandidateResultsResource)
    POST    /modelResults/update/{id} (org.deeplearning4j.arbiter.optimize.ui.resources.CandidateResultsResource)
    GET     /summary (org.deeplearning4j.arbiter.optimize.ui.resources.SummaryStatusResource)
    POST    /summary/update (org.deeplearning4j.arbiter.optimize.ui.resources.SummaryStatusResource)
    GET     /lastUpdate (org.deeplearning4j.arbiter.optimize.ui.resources.LastUpdateResource)
    POST    /lastUpdate/update (org.deeplearning4j.arbiter.optimize.ui.resources.LastUpdateResource)
    GET     /arbiter (org.deeplearning4j.arbiter.optimize.ui.ArbiterUIResource)

INFO  [2016-08-07 19:50:35,886] org.eclipse.jetty.server.handler.ContextHandler: Started i.d.j.MutableServletContextHandler@10db6131{/,null,AVAILABLE}
INFO  [2016-08-07 19:50:35,892] io.dropwizard.setup.AdminEnvironment: tasks = 

    POST    /tasks/log-level (io.dropwizard.servlets.tasks.LogConfigurationTask)
    POST    /tasks/gc (io.dropwizard.servlets.tasks.GarbageCollectionTask)

WARN  [2016-08-07 19:50:35,893] io.dropwizard.setup.AdminEnvironment: 
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
!    THIS APPLICATION HAS NO HEALTHCHECKS. THIS MEANS YOU WILL NEVER KNOW      !
!     IF IT DIES IN PRODUCTION, WHICH MEANS YOU WILL NEVER KNOW IF YOU'RE      !
!    LETTING YOUR USERS DOWN. YOU SHOULD ADD A HEALTHCHECK FOR EACH OF YOUR    !
!         APPLICATION'S DEPENDENCIES WHICH FULLY (BUT LIGHTLY) TESTS IT.       !
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
INFO  [2016-08-07 19:50:35,912] org.eclipse.jetty.server.handler.ContextHandler: Started i.d.j.MutableServletContextHandler@2f0bfe17{/,null,AVAILABLE}
INFO  [2016-08-07 19:50:35,943] org.eclipse.jetty.server.ServerConnector: Started application@53ac845a{HTTP/1.1}{0.0.0.0:8080}
INFO  [2016-08-07 19:50:35,946] org.eclipse.jetty.server.ServerConnector: Started admin@3cee53dc{HTTP/1.1}{0.0.0.0:8081}
INFO  [2016-08-07 19:50:35,947] org.eclipse.jetty.server.Server: Started @8129ms
INFO  [2016-08-07 19:50:36,924] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: BaseOptimizationRunner: execution started
INFO  [2016-08-07 19:50:40,497] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:40,985] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:41,355] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:41,788] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:42,057] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:42,166] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 0, score = 0.6826923076923077
INFO  [2016-08-07 19:50:42,167] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: New best score: 0.6826923076923077 (first completed model)
INFO  [2016-08-07 19:50:42,498] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:42,725] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:42,952] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:43,161] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:43,315] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:43,364] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 1, score = 0.6121794871794872
INFO  [2016-08-07 19:50:43,561] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:43,902] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:44,066] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:44,795] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:45,342] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:45,511] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 2, score = 0.6666666666666666
INFO  [2016-08-07 19:50:46,218] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:48,108] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:48,450] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:48,674] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:48,976] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:49,090] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 3, score = 0.6730769230769231
INFO  [2016-08-07 19:50:49,330] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:49,542] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:49,710] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:49,866] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:50,487] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:50,538] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 4, score = 0.6121794871794872
INFO  [2016-08-07 19:50:50,758] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:50,904] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:51,046] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:51,186] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:51,327] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:51,363] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 5, score = 0.6121794871794872
INFO  [2016-08-07 19:50:51,539] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:51,679] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:51,821] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:51,963] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:52,094] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:52,119] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 6, score = 0.6121794871794872
INFO  [2016-08-07 19:50:52,352] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:52,494] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:52,637] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:52,784] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:52,929] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:52,962] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 7, score = 0.6121794871794872
INFO  [2016-08-07 19:50:53,160] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:53,304] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:53,469] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:53,612] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:53,762] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:53,793] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 8, score = 0.6121794871794872
INFO  [2016-08-07 19:50:53,974] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:54,117] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:54,297] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:54,444] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:54,600] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:54,628] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 9, score = 0.6121794871794872
INFO  [2016-08-07 19:50:54,834] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:54,988] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:55,144] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:55,295] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:55,448] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:55,478] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 10, score = 0.6121794871794872
INFO  [2016-08-07 19:50:55,662] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:55,811] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:55,961] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:56,794] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:57,104] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:57,141] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 11, score = 0.592948717948718
INFO  [2016-08-07 19:50:57,358] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:57,493] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:57,632] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:57,783] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:57,976] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:58,009] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 12, score = 0.6121794871794872
INFO  [2016-08-07 19:50:58,218] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:58,374] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:58,532] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:58,732] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:58,875] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:58,902] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 13, score = 0.6858974358974359
INFO  [2016-08-07 19:50:58,902] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: New best score: 0.6858974358974359 (prev=0.6826923076923077)
INFO  [2016-08-07 19:50:59,061] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:50:59,205] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:50:59,352] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:50:59,499] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:50:59,657] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:50:59,683] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 14, score = 0.6121794871794872
INFO  [2016-08-07 19:50:59,876] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:00,090] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:00,307] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:00,446] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:00,585] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:00,610] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 15, score = 0.6121794871794872
INFO  [2016-08-07 19:51:00,789] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:00,941] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:01,150] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:01,314] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:01,464] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:01,491] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 16, score = 0.6121794871794872
INFO  [2016-08-07 19:51:01,740] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:01,916] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:02,056] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:02,216] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:02,409] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:02,439] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 17, score = 0.6121794871794872
INFO  [2016-08-07 19:51:02,694] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:02,886] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:03,031] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:03,175] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:03,529] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:03,556] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 18, score = 0.6121794871794872
INFO  [2016-08-07 19:51:03,728] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:03,869] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:04,009] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:04,196] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:04,373] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:04,397] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 19, score = 0.6121794871794872
INFO  [2016-08-07 19:51:04,618] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:04,798] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:05,212] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:05,517] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:05,697] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:05,726] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 20, score = 0.6121794871794872
INFO  [2016-08-07 19:51:05,987] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:06,190] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:06,566] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:06,937] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:07,248] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:07,283] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 21, score = 0.6121794871794872
INFO  [2016-08-07 19:51:07,436] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:07,583] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:07,804] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:08,042] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:08,214] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:08,292] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 22, score = 0.6923076923076923
INFO  [2016-08-07 19:51:08,292] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: New best score: 0.6923076923076923 (prev=0.6858974358974359)
INFO  [2016-08-07 19:51:08,482] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:08,836] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:09,248] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:09,591] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:09,799] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:09,825] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 23, score = 0.6666666666666666
INFO  [2016-08-07 19:51:10,225] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:10,594] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:10,780] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:11,063] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:11,332] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:11,372] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 24, score = 0.6121794871794872
INFO  [2016-08-07 19:51:11,901] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:12,571] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:13,045] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:13,527] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:13,720] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:13,752] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 25, score = 0.6923076923076923
INFO  [2016-08-07 19:51:13,938] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:14,113] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:14,335] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:14,560] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:14,717] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:14,752] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 26, score = 0.6923076923076923
INFO  [2016-08-07 19:51:15,042] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:15,257] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:15,410] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:15,574] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:15,725] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:15,755] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 27, score = 0.6121794871794872
INFO  [2016-08-07 19:51:16,239] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:16,470] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:16,728] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:16,918] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:17,113] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:17,146] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 28, score = 0.657051282051282
INFO  [2016-08-07 19:51:17,438] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 1, number of batches completed 116
INFO  [2016-08-07 19:51:17,658] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 2, number of batches completed 116
INFO  [2016-08-07 19:51:17,808] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 3, number of batches completed 116
INFO  [2016-08-07 19:51:17,957] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 4, number of batches completed 116
INFO  [2016-08-07 19:51:18,099] org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Epoch 5, number of batches completed 116
INFO  [2016-08-07 19:51:18,122] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Completed task 29, score = 0.6121794871794872
INFO  [2016-08-07 19:51:18,130] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: BaseOptimizationRunner global termination condition hit: MaxCandidatesCondition(30)
INFO  [2016-08-07 19:51:18,130] org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner: Optimization runner: execution complete
Best score: 0.6923076923076923
Index of model with best score: 22
Number of configurations evaluated: 30



Configuration of best model:

{
  "backprop" : true,
  "backpropType" : "Standard",
  "confs" : [ {
    "extraArgs" : [ 0 ],
    "l1ByParam" : {
      "b" : 0.0,
      "W" : 0.0
    },
    "l2ByParam" : {
      "b" : 0.0,
      "W" : 1.0E-4
    },
    "layer" : {
      "dense" : {
        "activationFunction" : "relu",
        "adamMeanDecay" : "NaN",
        "adamVarDecay" : "NaN",
        "biasInit" : 0.0,
        "biasL1" : 0.0,
        "biasL2" : 0.0,
        "biasLearningRate" : 0.021107968650120837,
        "dist" : null,
        "dropOut" : 0.0,
        "gradientNormalization" : "None",
        "gradientNormalizationThreshold" : 1.0,
        "l1" : 0.0,
        "l2" : 1.0E-4,
        "layerName" : null,
        "learningRate" : 0.021107968650120837,
        "learningRateSchedule" : null,
        "momentum" : "NaN",
        "momentumSchedule" : null,
        "nin" : 12,
        "nout" : 8,
        "rho" : "NaN",
        "rmsDecay" : "NaN",
        "updater" : "SGD",
        "weightInit" : "XAVIER"
      }
    },
    "leakyreluAlpha" : 0.0,
    "learningRateByParam" : {
      "b" : 0.021107968650120837,
      "W" : 0.021107968650120837
    },
    "learningRatePolicy" : "None",
    "lrPolicyDecayRate" : "NaN",
    "lrPolicyPower" : "NaN",
    "lrPolicySteps" : "NaN",
    "maxNumLineSearchIterations" : 5,
    "miniBatch" : true,
    "minimize" : true,
    "numIterations" : 1,
    "optimizationAlgo" : "STOCHASTIC_GRADIENT_DESCENT",
    "seed" : 1470599467289,
    "stepFunction" : null,
    "useDropConnect" : false,
    "useRegularization" : true,
    "variables" : [ "W", "b" ]
  }, {
    "extraArgs" : [ 0 ],
    "l1ByParam" : {
      "b" : 0.0,
      "W" : 0.0
    },
    "l2ByParam" : {
      "b" : 0.0,
      "W" : 1.0E-4
    },
    "layer" : {
      "dense" : {
        "activationFunction" : "relu",
        "adamMeanDecay" : "NaN",
        "adamVarDecay" : "NaN",
        "biasInit" : 0.0,
        "biasL1" : 0.0,
        "biasL2" : 0.0,
        "biasLearningRate" : 0.021107968650120837,
        "dist" : null,
        "dropOut" : 0.0,
        "gradientNormalization" : "None",
        "gradientNormalizationThreshold" : 1.0,
        "l1" : 0.0,
        "l2" : 1.0E-4,
        "layerName" : null,
        "learningRate" : 0.021107968650120837,
        "learningRateSchedule" : null,
        "momentum" : "NaN",
        "momentumSchedule" : null,
        "nin" : 8,
        "nout" : 4,
        "rho" : "NaN",
        "rmsDecay" : "NaN",
        "updater" : "SGD",
        "weightInit" : "XAVIER"
      }
    },
    "leakyreluAlpha" : 0.0,
    "learningRateByParam" : {
      "b" : 0.021107968650120837,
      "W" : 0.021107968650120837
    },
    "learningRatePolicy" : "None",
    "lrPolicyDecayRate" : "NaN",
    "lrPolicyPower" : "NaN",
    "lrPolicySteps" : "NaN",
    "maxNumLineSearchIterations" : 5,
    "miniBatch" : true,
    "minimize" : true,
    "numIterations" : 1,
    "optimizationAlgo" : "STOCHASTIC_GRADIENT_DESCENT",
    "seed" : 1470599467289,
    "stepFunction" : null,
    "useDropConnect" : false,
    "useRegularization" : true,
    "variables" : [ "W", "b" ]
  }, {
    "extraArgs" : [ ],
    "l1ByParam" : {
      "b" : 0.0,
      "W" : 0.0
    },
    "l2ByParam" : {
      "b" : 0.0,
      "W" : 1.0E-4
    },
    "layer" : {
      "output" : {
        "activationFunction" : "softmax",
        "adamMeanDecay" : "NaN",
        "adamVarDecay" : "NaN",
        "biasInit" : 0.0,
        "biasL1" : 0.0,
        "biasL2" : 0.0,
        "biasLearningRate" : 0.021107968650120837,
        "customLossFunction" : null,
        "dist" : null,
        "dropOut" : 0.0,
        "gradientNormalization" : "None",
        "gradientNormalizationThreshold" : 1.0,
        "l1" : 0.0,
        "l2" : 1.0E-4,
        "layerName" : null,
        "learningRate" : 0.021107968650120837,
        "learningRateSchedule" : null,
        "lossFunction" : "NEGATIVELOGLIKELIHOOD",
        "momentum" : "NaN",
        "momentumSchedule" : null,
        "nin" : 4,
        "nout" : 2,
        "rho" : "NaN",
        "rmsDecay" : "NaN",
        "updater" : "SGD",
        "weightInit" : "XAVIER"
      }
    },
    "leakyreluAlpha" : 0.0,
    "learningRateByParam" : {
      "b" : 0.021107968650120837,
      "W" : 0.021107968650120837
    },
    "learningRatePolicy" : "None",
    "lrPolicyDecayRate" : "NaN",
    "lrPolicyPower" : "NaN",
    "lrPolicySteps" : "NaN",
    "maxNumLineSearchIterations" : 5,
    "miniBatch" : true,
    "minimize" : true,
    "numIterations" : 1,
    "optimizationAlgo" : "STOCHASTIC_GRADIENT_DESCENT",
    "seed" : 1470599467289,
    "stepFunction" : null,
    "useDropConnect" : false,
    "useRegularization" : true,
    "variables" : [ "W", "b" ]
  } ],
  "inputPreProcessors" : { },
  "pretrain" : false,
  "redistributeParams" : false,
  "tbpttBackLength" : 20,
  "tbpttFwdLength" : 20
}

Module POM

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <parent>
        <artifactId>dl4j-lab</artifactId>
        <groupId>com.danlin</groupId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <modelVersion>4.0.0</modelVersion>

    <artifactId>dl4j</artifactId>

    <dependencyManagement>
        <dependencies>
            <dependency>
                <groupId>org.nd4j</groupId>
                <artifactId>nd4j-native-platform</artifactId>
                <version>${nd4j.version}</version>
            </dependency>
            <dependency>
                <groupId>org.nd4j</groupId>
                <artifactId>nd4j-cuda-7.5-platform</artifactId>
                <version>${nd4j.version}</version>
            </dependency>
            <!--<dependency>-->
                <!--<groupId>com.fasterxml.jackson.core</groupId>-->
                <!--<artifactId>jackson-databind</artifactId>-->
                <!--<version>2.4.4</version>-->
            <!--</dependency>-->
        </dependencies>
    </dependencyManagement>

    <dependencies>
        <!-- ND4J backend. You need one in every DL4J project. Normally define artifactId as either "nd4j-native-platform" or "nd4j-cuda-7.5-platform" -->
        <dependency>
            <groupId>org.nd4j</groupId>
            <artifactId>${nd4j.backend}</artifactId>
        </dependency>

        <!-- Core DL4J functionality -->
        <dependency>
            <groupId>org.deeplearning4j</groupId>
            <artifactId>deeplearning4j-core</artifactId>
            <version>${dl4j.version}</version>
        </dependency>

        <dependency>
            <groupId>org.deeplearning4j</groupId>
            <artifactId>deeplearning4j-nlp</artifactId>
            <version>${dl4j.version}</version>
        </dependency>

        <!-- deeplearning4j-ui is used for HistogramIterationListener + visualization: see http://deeplearning4j.org/visualization -->
        <dependency>
            <groupId>org.deeplearning4j</groupId>
            <artifactId>deeplearning4j-ui</artifactId>
            <version>${dl4j.version}</version>
        </dependency>

        <!-- Force guava versions for using UI/HistogramIterationListener -->
        <dependency>
            <groupId>com.google.guava</groupId>
            <artifactId>guava</artifactId>
            <version>${guava.version}</version>
        </dependency>

        <!-- datavec-data-codec: used only in video example for loading video data -->
        <dependency>
            <artifactId>datavec-data-codec</artifactId>
            <groupId>org.datavec</groupId>
            <version>${datavec.version}</version>
        </dependency>

        <!-- Used in the feedforward/classification/MLP* and feedforward/regression/RegressionMathFunctions example -->
        <dependency>
            <groupId>jfree</groupId>
            <artifactId>jfreechart</artifactId>
            <version>${jfreechart.version}</version>
        </dependency>

        <!-- Arbiter: used for hyperparameter optimization examples -->
        <dependency>
            <groupId>org.deeplearning4j</groupId>
            <artifactId>arbiter-deeplearning4j</artifactId>
            <version>${arbiter.version}</version>
        </dependency>
    </dependencies>

    <build>
        <plugins>
            <plugin>
                <groupId>org.codehaus.mojo</groupId>
                <artifactId>exec-maven-plugin</artifactId>
                <version>${exec-maven-plugin.version}</version>
                <executions>
                    <execution>
                        <goals>
                            <goal>exec</goal>
                        </goals>
                    </execution>
                </executions>
                <configuration>
                    <executable>java</executable>
                </configuration>
            </plugin>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-shade-plugin</artifactId>
                <version>${maven-shade-plugin.version}</version>
                <configuration>
                    <shadedArtifactAttached>true</shadedArtifactAttached>
                    <shadedClassifierName>${shadedClassifier}</shadedClassifierName>
                    <createDependencyReducedPom>true</createDependencyReducedPom>
                    <filters>
                        <filter>
                            <artifact>*:*</artifact>
                            <excludes>
                                <exclude>org/datanucleus/**</exclude>
                                <exclude>META-INF/*.SF</exclude>
                                <exclude>META-INF/*.DSA</exclude>
                                <exclude>META-INF/*.RSA</exclude>
                            </excludes>
                        </filter>
                    </filters>
                </configuration>
                <executions>
                    <execution>
                        <phase>package</phase>
                        <goals>
                            <goal>shade</goal>
                        </goals>
                        <configuration>
                            <transformers>
                                <transformer
                                        implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
                                    <resource>reference.conf</resource>
                                </transformer>
                                <transformer
                                        implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer"/>
                                <transformer
                                        implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
                                </transformer>
                            </transformers>
                        </configuration>
                    </execution>
                </executions>
            </plugin>

            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.5.1</version>
                <configuration>
                    <source>1.8</source>
                    <target>1.8</target>
                </configuration>
            </plugin>
        </plugins>
    </build>

</project>

Parent POM

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>com.danlin</groupId>
    <artifactId>dl4j-lab</artifactId>
    <packaging>pom</packaging>
    <version>1.0-SNAPSHOT</version>

    <modules>
        <module>datavec</module>
        <module>dl4j</module>
    </modules>

    <properties>
        <nd4j.backend>nd4j-native-platform</nd4j.backend>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <shadedClassifier>bin</shadedClassifier>
        <java.version>1.7</java.version>
        <nd4j.version>0.5.0</nd4j.version>
        <dl4j.version>0.5.0</dl4j.version>
        <datavec.version>0.4.0</datavec.version>
        <arbiter.version>0.5.0</arbiter.version>
        <guava.version>19.0</guava.version>
        <jfreechart.version>1.0.13</jfreechart.version>
        <maven-shade-plugin.version>2.4.3</maven-shade-plugin.version>
        <exec-maven-plugin.version>1.4.0</exec-maven-plugin.version>

        <scala.binary.version>2.10</scala.binary.version>
    </properties>


</project>